What is incident response? A complete guide

Copyright TechTarget - All rights reserved https://cyber.law.harvard.edu/rss/rss.html Techtarget Feed Generator en Sat, 13 Jun 2026 20:15:26 GMT https://www.techtarget.com/whatis editor@techtarget.com <p>Incident response is an organized, strategic approach to detecting and managing cyberattacks in ways that minimize damage, recovery time and total costs.</p> <p><a href="https://www.techtarget.com/searchsecurity/tip/Incident-management-vs-incident-response-explained">Incident response is a subset of incident management</a>. <i>Incident management</i> is an umbrella term for an enterprise's broad handling of cyberattacks, involving diverse stakeholders from the executive, legal, HR, communications and IT teams. <i>Incident response</i> is the part of incident management that handles technical cybersecurity tasks and considerations.</p> <p>Many experts use the terms <i>incident response </i>and <i>incident management</i> interchangeably because both aim to ensure <a href="https://www.techtarget.com/searchdisasterrecovery/definition/business-continuity">business continuity</a> in the face of a security crisis, such as a data breach. Yet <a href="https://www.techtarget.com/searchsecurity/tip/Business-continuity-vs-disaster-recovery-vs-incident-response">incident response, business continuity and disaster recovery</a> measures play distinct, if complementary, roles in keeping organizations operational despite interruptions. Consider how their primary goals differ:</p> <ul type="disc" class="default-list"> <li><b>Business continuity.</b> Aims to maintain critical business operations in the face of any kind of expected or unexpected disruption -- e.g., a natural disaster, planned downtime or a cyberattack.</li> <li><b>Disaster recovery.</b> Aims to restore IT functionality after any kind of unexpected disruption -- e.g., a natural disaster, a technological outage or a cyberattack.</li> <li><b>Incident response.</b> Aims to identify, contain and resolve cyberattacks and any problems they cause.</li> </ul> <p>Digital forensics and incident response (<a href="https://www.techtarget.com/searchsecurity/definition/digital-forensics-and-incident-response-DFIR">DFIR</a>) is an approach to incident response that integrates digital forensics tools and processes. Digital forensics is a subset of forensic science that involves the collection and analysis of data to fully understand a cyberevent, as well as the preservation of evidence for future internal use -- such as for reconstruction of a security event -- and external use -- for example, as digital evidence in court.</p> <p>Data uncovered through DFIR practices can give incident responders a clearer, more accurate understanding of a security incident, leading to faster recovery, less disruption and a stronger security posture.</p> <figure class="main-article-image full-col" data-img-fullsize="https://www.techtarget.com/rms/onlineimages/business_continuity_plan_vs_disaster_recovery_plan_vs_incident_response_plan-f.png"> <img data-src="https://www.techtarget.com/rms/onlineimages/business_continuity_plan_vs_disaster_recovery_plan_vs_incident_response_plan-f_mobile.png" class="lazy" data-srcset="https://www.techtarget.com/rms/onlineimages/business_continuity_plan_vs_disaster_recovery_plan_vs_incident_response_plan-f_mobile.png 960w,https://www.techtarget.com/rms/onlineimages/business_continuity_plan_vs_disaster_recovery_plan_vs_incident_response_plan-f.png 1280w" alt="Graphic with text explaining the differences among business continuity, disaster recovery and incident response." height="258" width="560"> <figcaption> <i class="icon pictures" data-icon="z"></i>While each is distinct, business continuity, disaster recovery and incident response all share the goal of keeping an organization running. </figcaption> <div class="main-article-image-enlarge"> <i class="icon" data-icon="w"></i> </div> </figure> <section class="section main-article-chapter" data-menu-title="Why is incident response important?"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Why is incident response important?</h2> <p>Today, Benjamin Franklin might say the only certainties are death, taxes and cyberattacks. Research suggests <a href="https://www.techtarget.com/whatis/34-Cybersecurity-Statistics-to-Lose-Sleep-Over-in-2020">critical security incidents are all but inevitable</a>, driven by both criminal ingenuity on the attacker's side and human error on the user's side. A reactive, disorganized response to an attack gives bad actors the upper hand and puts the business at greater risk. At worst, the financial, operational and reputational damage from a major security incident could put an organization out of business.</p> <p>On the other hand, a cohesive, well-vetted incident response strategy that follows <a href="https://www.techtarget.com/searchsecurity/tip/Incident-response-best-practices-for-your-organization">incident response best practices</a> limits fallout and positions the business to recover as quickly as possible.</p> <div class="youtube-iframe-container"> <iframe id="ytplayer-0" src="https://www.youtube.com/embed/EtfdkP-JDAA?autoplay=0&modestbranding=1&rel=0&widget_referrer=null&enablejsapi=1&origin=https://www.techtarget.com" type="text/html" height="360" width="640" frameborder="0" loading="lazy"></iframe> </div> <h3>Types of security incidents</h3> <p>In developing incident response strategies, it's important to first understand how vulnerabilities, threats, incidents and data breaches relate.</p> <p>A <i>vulnerability</i> is a weakness in the IT or business environment. A <i>threat</i> is an entity -- whether a malicious hacker or a company insider -- that aims to exploit a vulnerability in an attack. To qualify as an <i>incident</i>, an attack must succeed in accessing enterprise resources or otherwise putting them at risk. Finally, a <i>data breach</i> is an incident in which attackers successfully compromise sensitive information, such as personally identifiable information or intellectual property.</p> <p>When it comes to cybersecurity, an ounce of prevention is worth a pound of cure. Experts say organizations should <a href="https://www.techtarget.com/searchsecurity/feature/How-to-fix-the-top-5-cybersecurity-vulnerabilities">fix known vulnerabilities</a> and proactively develop response strategies for dealing with the following <a href="https://www.techtarget.com/searchsecurity/feature/10-types-of-security-incidents-and-how-to-handle-them">common security incidents</a>:</p> <ul type="disc" class="default-list"> <li>Unauthorized attempts to access systems or data.</li> <li>Privilege escalation attacks.</li> <li><a href="https://www.techtarget.com/searchsecurity/definition/insider-threat">Insider threats</a>.</li> <li><a href="https://www.techtarget.com/searchsecurity/definition/phishing">Phishing</a> attacks.</li> <li>Malware attacks.</li> <li>Denial-of-service (<a href="https://www.techtarget.com/searchsecurity/definition/denial-of-service">DoS</a>) attacks.</li> <li><a href="https://www.techtarget.com/iotagenda/definition/man-in-the-middle-attack-MitM">Man-in-the-middle attacks</a>.</li> <li>Password attacks.</li> <li>Web application attacks.</li> <li><a href="https://www.techtarget.com/searchsecurity/definition/advanced-persistent-threat-APT">Advanced persistent threats</a>.</li> </ul> <p>Since not all security events are equally serious, and because enterprises simply do not have the resources to aggressively address each and every one, incident response requires prioritization. Weigh an incident's urgency and importance to determine if it warrants a full-fledged response. For example, an active ransomware attack is both urgent -- i.e., time-sensitive -- and important -- i.e., it can put critical IT assets and business continuity at risk. Such an attack logically warrants a major, expedited response.</p> <p><i>Learn more about the </i><a href="https://www.techtarget.com/searchsecurity/feature/Top-10-types-of-information-security-threats-for-IT-teams"><i>top cybersecurity threats</i></a><i> enterprises face today.</i></p> </section> <section class="section main-article-chapter" data-menu-title="What is an incident response plan?"> <h2 class="section-title"><i class="icon" data-icon="1"></i>What is an incident response plan?</h2> <p>An incident response plan is an organization's go-to documentation that details the following:</p> <ul type="disc" class="default-list"> <li><b>What. </b>Which threats, exploits and situations qualify as actionable security incidents, and what to do when they occur.</li> <li><b>Who. </b>In the event of a security incident, who is responsible for which tasks and how others can contact them.</li> <li><b>When. </b>Under what circumstances team members should perform given response tasks.</li> <li><b>How. </b>Specifically, how team members should complete those tasks.</li> </ul> <p>An incident response plan acts as a detailed, authoritative map that guides responders from initial detection, assessment and triage of an incident to its containment and resolution.</p> </section> <section class="section main-article-chapter" data-menu-title="How to create an incident response plan"> <h2 class="section-title"><i class="icon" data-icon="1"></i>How to create an incident response plan</h2> <p>Successful <a href="https://www.techtarget.com/searchsecurity/feature/5-critical-steps-to-creating-an-effective-incident-response-plan">incident response requires proactively drafting, vetting and testing plans</a> <i>before</i> a crisis strikes. Best practices include the following:</p> <figure class="main-article-image half-col" data-img-fullsize="https://www.techtarget.com/rms/onlineimages/security-incident_response_plan_checklist.png"> <img data-src="https://www.techtarget.com/rms/onlineimages/security-incident_response_plan_checklist_half_column_mobile.png" class="lazy" data-srcset="https://www.techtarget.com/rms/onlineimages/security-incident_response_plan_checklist_half_column_mobile.png 960w,https://www.techtarget.com/rms/onlineimages/security-incident_response_plan_checklist.png 1280w" alt="Graphic of an incident response plan checklist" height="234" width="279"> <figcaption> <i class="icon pictures" data-icon="z"></i>An incident response plan is a key component of any incident response program. </figcaption> <div class="main-article-image-enlarge"> <i class="icon" data-icon="w"></i> </div> </figure> <ol type="1" start="1" class="default-list"> <li><b>Establish a policy.</b> An incident remediation and response policy should be an evergreen document describing general, high-level incident-handling priorities. A good policy empowers incident responders and guides them to make sound decisions when the proverbial excrement hits the fan.</li> <li><b>Build an incident response team.</b> An incident response plan is only as strong as the people involved. Establish who will handle which tasks, and ensure everyone has adequate training to fulfill their roles and responsibilities.</li> <li><b>Create playbooks.</b> Playbooks are the lifeblood of incident response. While an incident response policy provides a high-level view, playbooks get into the weeds, outlining standardized, step-by-step actions responders should take in specific scenarios. Playbook benefits include greater consistency, efficiency and effectiveness -- in both incident response and incident-responder training.<br><br><i>Learn </i><a href="https://www.techtarget.com/searchsecurity/tip/How-to-create-an-incident-response-playbook"><i>how to create playbooks</i></a><i>.</i></li> <li><b>Create a communication plan. </b>Incident response can't succeed without a <a href="https://www.techtarget.com/searchsecurity/tip/Incident-response-How-to-implement-a-communication-plan">solid communication plan</a> among diverse stakeholders. These could include members of the security, executive, communications, legal and HR teams, as well as customers, third-party partners, law enforcement and the public.</li> </ol> <p>An incident response plan should generally include the following components:</p> <ul type="disc" class="default-list"> <li>A plan overview.</li> <li>A list of roles and responsibilities.</li> <li>A list of incidents requiring action.</li> <li>The current state of network infrastructure and security controls.</li> <li>Detection, investigation and containment procedures.</li> <li>Eradication procedures.</li> <li>Recovery procedures.</li> <li>The breach notification process.</li> <li>A list of post-incident follow-up tasks.</li> <li>A contact list.</li> <li>Incident response plan testing.</li> <li>Ongoing revisions.</li> </ul> </section> <section class="section main-article-chapter" data-menu-title="How to manage an incident response plan"> <h2 class="section-title"><i class="icon" data-icon="1"></i>How to manage an incident response plan</h2> <p>The worst time to discover an incident response plan has holes is during a real security crisis, which makes ongoing testing critical. Experts advise organizations to perform regular simulations featuring diverse attack vectors, such as ransomware, malicious insiders and brute-force attacks.</p> <p>Many enterprises <a href="https://www.techtarget.com/searchsecurity/tip/How-to-conduct-incident-response-tabletop-exercises">conduct incident response tabletop exercises</a> to vet their plans. A discussion-based tabletop exercise involves talking through the specifics of an attack and the team's response. An operational tabletop exercise includes hands-on tasks, with enactment of relevant processes to see how they unfold.</p> <p><i>Use templates, </i><a href="https://cdn.ttgtmedia.com/rms/editorial/Incident_Response_Tabletop_Exercise_Template.docx"><i>such as this one</i></a><i>, to plan effective simulations.</i></p> <p>After both simulated and real security incidents, response teams should do the following:</p> <ul type="disc" class="default-list"> <li>Study what happened and identify lessons learned.</li> <li>Review <a href="https://www.techtarget.com/searchsecurity/tip/The-best-incident-response-metrics-and-how-to-use-them">key incident response metrics</a> -- e.g., mean time to detect, mean time to identify, mean time to respond, mean time to contain, total cost, etc. -- and analyze how metrics from the recent incident compare.</li> <li><a href="https://www.techtarget.com/searchsecurity/feature/Top-reasons-incident-response-plans-fail">Note any security gaps that emerged</a>.</li> <li>Recommend additional controls.</li> <li>Brainstorm ways to improve processes.</li> <li>Update the incident response plan accordingly.</li> </ul> <p>Remember, an incident response plan is not a set-it-and-forget-it proposition. It should continually evolve to reflect changes in the threat landscape, IT infrastructure and business environment. Experts recommend formal, comprehensive reassessments and revisions annually, at the very least.</p> </section> <section class="section main-article-chapter" data-menu-title="Incident response frameworks: Phases of incident response"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Incident response frameworks: Phases of incident response</h2> <p>Rather than reinventing the wheel, an organization building an incident response plan can refer to <a href="https://www.techtarget.com/searchsecurity/tip/Incident-response-frameworks-for-enterprise-security-teams">established incident response frameworks</a> for high-level guidance and direction.</p> <p>Well-known frameworks from NIST, ISO and SANS Institute differ slightly in their approaches, yet they each describe similar phases of incident response:</p> <ol type="1" start="1" class="default-list"> <li><b>Preparation/planning.</b> Build an incident response team and create policies, processes and playbooks; deploy tools and services to support incident response.</li> <li><b>Detection/identification. </b>Use IT monitoring to detect, evaluate, validate and triage security incidents.</li> <li><b>Containment. </b>Take steps to stop an incident from worsening and regain control of IT resources.</li> <li><b>Eradication. </b>Eliminate threat activity, including malware and malicious user accounts; identify any vulnerabilities the attackers exploited.</li> <li><b>Recovery. </b>Restore normal operations and mitigate relevant vulnerabilities.</li> <li><b>Lessons learned. </b>Review the incident to establish what happened, when it happened and how it happened. Flag security controls, policies and procedures that failed to meet expectations and identify ways to improve them. Update the incident response plan accordingly.</li> </ol> </section> <section class="section main-article-chapter" data-menu-title="Who is responsible for incident response?"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Who is responsible for incident response?</h2> <p>Behind every great incident response program is a coordinated, efficient and effective <a href="https://www.techtarget.com/searchsecurity/definition/incident-response-team">incident response team</a>. After all, without the right people to support them and put them into practice, security policies, processes and tools mean very little. This cross-functional group consists of people from across the organization who are responsible for completing the steps and processes involved in incident response.</p> <h3>Types of incident response teams</h3> <p>The three most common types of incident response teams are computer security incident response team (<a href="https://www.techtarget.com/whatis/definition/Computer-Security-Incident-Response-Team-CSIRT">CSIRT</a>), computer incident response team (CIRT) and computer emergency response team (<a href="https://www.techtarget.com/whatis/definition/CERT-Computer-Emergency-Readiness-Team">CERT</a>).</p> <p>These acronyms are often used interchangeably in the field, and the teams generally have the same goals and responsibilities. One important note is that the name <i>CERT</i> is a registered trademark of Carnegie Mellon University, so companies must apply for authorization to use it.</p> <p>Another term commonly used in incident response team conversations is <i>security operations center</i> (<a href="https://www.techtarget.com/searchsecurity/definition/Security-Operations-Center-SOC">SOC</a>). A SOC encompasses the people, tools and processes that manage an organization's security program. While SOC teams might be responsible for incident response, it is not their sole task within an organization. SOC teams' duties can also include conducting asset discovery and management, keeping activity logs and ensuring regulatory compliance, among others.</p> <p><i>Learn more about </i><a href="https://www.techtarget.com/searchsecurity/tip/CERT-vs-CSIRT-vs-SOC-Whats-the-difference"><i>CSIRTs, CIRTs, CERTs and SOCs</i></a><i>.</i></p> <h3>Incident response team members</h3> <p>The <a href="https://www.techtarget.com/searchsecurity/feature/How-to-build-an-incident-response-team-for-your-organization">size of an incident response team and the members included</a> will vary based on the individual organization's needs. Some members could even fill multiple roles and responsibilities.</p> <p>In general, an incident response team consists of the following members:</p> <ul type="disc" class="default-list"> <li><b>Technical team.</b> This is the core incident response team of IT and security members who have technical expertise across company systems. It often includes an incident response manager, incident response coordinator, team lead, security analysts, incident responders, threat researchers and forensic analysts.</li> <li><b>Executive sponsor.</b> This is an executive or board member, often the CSO or CISO.</li> <li><b>Communications team.</b> This includes PR representatives and others who manage internal and external communications.</li> <li><b>External stakeholders.</b> Members include other employees or departments within the organization, such as IT, legal or general counsel, HR, PR, business continuity and disaster recovery, physical security and facilities teams.</li> <li><b>Third parties.</b> These external members might include security or incident response consultants, external legal representation, MSPs, managed security service providers, cloud service providers (CSPs), vendors and partners.</li> </ul> <figure class="main-article-image full-col" data-img-fullsize="https://www.techtarget.com/rms/onlineImages/pillar_incident_response_team.png"> <img data-src="https://www.techtarget.com/rms/onlineImages/pillar_incident_response_team_mobile.png" class="lazy" data-srcset="https://www.techtarget.com/rms/onlineImages/pillar_incident_response_team_mobile.png 960w,https://www.techtarget.com/rms/onlineImages/pillar_incident_response_team.png 1280w" alt="Graphic with text explaining how to build an incident response team" height="324" width="560"> <figcaption> <i class="icon pictures" data-icon="z"></i>A well-developed incident response team is vital to ensuring incident response activities happen as planned. </figcaption> <div class="main-article-image-enlarge"> <i class="icon" data-icon="w"></i> </div> </figure> <h3>What does an incident response team do?</h3> <p>The main goals of an incident response team are to detect and respond to security events and minimize their business impact. As such, team responsibilities largely align with the phases outlined in an incident response framework and plan. Team tasks include the following:</p> <ul type="disc" class="default-list"> <li>Prepare for and prevent security incidents.</li> <li>Create the incident response plan.</li> <li>Test, update and manage the incident response plan before use.</li> <li>Perform incident response tabletop exercises.</li> <li>Develop metrics to analyze program initiatives.</li> <li>Identify security events.</li> <li>Contain security events, quarantine threats and isolate systems.</li> <li>Eradicate threats, discover root causes and remove affected systems from production environments.</li> <li>Recover from threats and get affected systems back online.</li> <li>Conduct follow-up activities, including documentation, incident analysis and identifying how to prevent similar events and improve future response efforts.</li> <li>Review and update the incident response plan regularly.</li> </ul> <div class="extra-info"> <div class="extra-info-inner"> <h3 class="splash-heading">Interested in becoming an incident responder?</h3> <p>Incident response requires professionals with security skills who can execute tasks such as monitoring for vulnerabilities and taking appropriate measures when necessary. They must be able to analyze data to identify and assess the scope and urgency of incidents, as well as perform other duties. Incident responders might also report on trends, educate internal users and work with law enforcement.</p> <p>The incident responder role can be an exciting, albeit challenging, career. Incident responder jobs are in demand and can command sizeable salaries. The tradeoff, however, is that many incident responders work long hours under constant stress.</p> <p>Learn more about the <a href="https://www.techtarget.com/searchsecurity/feature/How-to-become-an-incident-responder-Requirements-and-more">incident responder career path</a>.</p> <p>Read up on <a href="https://www.techtarget.com/searchsecurity/tip/Top-incident-response-certifications-to-consider">incident response certifications</a>.</p> <p>Headed to an interview? Check out these <a href="https://www.techtarget.com/searchsecurity/feature/Top-5-incident-response-interview-questions">sample interview questions</a>.</p> </div> </div> </section> <section class="section main-article-chapter" data-menu-title="Incident response in the cloud"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Incident response in the cloud</h2> <p>As enterprise cloud use proliferates, the importance of including the cloud in incident response processes increases. The goals of cloud incident response are the same as in traditional incident response but with some caveats.</p> <p>Consider the shared responsibility model, for example. With on-premises applications, platforms and infrastructure, an organization's IT and security teams are generally responsible for all management and security tasks. With <a href="https://www.techtarget.com/whatis/SaaS-IaaS-PaaS-Comparing-Cloud-Service-Models">SaaS, PaaS and IaaS</a>, on the other hand, some or all responsibility shifts to CSPs. This can make incident detection and investigation more difficult or even impossible, depending on the deployment.</p> <p>Cloud incident response might also require new tools and skill sets, as well as a deeper knowledge of <a href="https://www.techtarget.com/searchsecurity/tip/Top-11-cloud-security-challenges-and-how-to-combat-them">cloud security incidents and threats</a>. Traditional tools might not work properly -- or at all -- in cloud environments. New tools and procedures not only add to what incident response teams must learn and manage but could also require extra budget.</p> <p><i>Learn more about </i><a href="https://www.techtarget.com/searchsecurity/tip/Cloud-incident-response-Frameworks-and-best-practices"><i>cloud incident response</i></a><i>, including the Cloud Security Alliance's framework and best practices for including the cloud in incident response programs.</i></p> </section> <section class="section main-article-chapter" data-menu-title="Incident response tools and technologies"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Incident response tools and technologies</h2> <p>As Benjamin Franklin once said, "The best investment is in the tools of one's own trade." In incident response, teams need a mix of tools and technologies -- many of which are likely already deployed in their security programs.</p> <p>To help decide which processes and tools will best prevent, detect, analyze, contain, eradicate and recover from incidents, many organizations rely on the military-derived <a href="https://www.techtarget.com/searchcio/definition/OODA-loop">OODA loop</a>, short for <i>observe</i>, <i>orient</i>, <i>decide</i> and <i>act</i>. This decision-making approach focuses on <a href="https://www.techtarget.com/searchsecurity/feature/Incident-response-tools-How-when-and-why-to-use-them">choosing incident response tools</a> that help teams gain visibility into systems, contextualize intelligence about threats, find the best response actions and carry out response.</p> <p>Typically categorized by their detection, prevention and response functionalities, incident response tools include the following:</p> <ul type="disc" class="default-list"> <li>Antimalware.</li> <li>Backup and recovery tools.</li> <li><a href="https://www.techtarget.com/searchcloudcomputing/definition/cloud-access-security-broker-CASB">Cloud access security broker</a>.</li> <li>Data classification tools.</li> <li><a href="https://www.techtarget.com/whatis/definition/data-loss-prevention-DLP">Data loss prevention</a>.</li> <li>DoS mitigation.</li> <li>Employee security awareness training.</li> <li>Endpoint detection and response.</li> <li>Firewalls.</li> <li>Forensic analysis.</li> <li>Intrusion prevention and detection systems.</li> <li>Security information and event management (<a href="https://www.techtarget.com/searchsecurity/definition/security-information-and-event-management-SIEM">SIEM</a>).</li> <li>Security orchestration, automation and response (SOAR).</li> <li>Vulnerability management.</li> </ul> <p>Managing all these tools can be a lot for a security team to handle. <a href="https://www.techtarget.com/searchsecurity/tip/Incident-response-automation-What-it-is-and-how-it-works">Automation in incident response</a> can help reduce alert fatigue, perform alert triage, automatically investigate and respond to threats, automate ticketing and alerting, conserve human efforts for higher-value activities, respond and resolve issues faster, automate case management and reporting, and save money. Automation and AI are becoming increasingly critical to defend against the increased velocity and volume of AI-enabled attacks.</p> <p>Contemplating whether to handle incident response in-house versus outsourcing some or all incident response duties? In-house incident response requires the proper staff, tools and budget. It's also important to consider the nature and complexity of the threats the organization faces. In some scenarios, in-house incident response might be the best bet. Organizations facing more serious threats, however -- or those that have multiple locations, each facing unique threats -- could be better served by outsourcing their incident response needs.</p> <p>Service providers often offer incident response services, such as the following, on retainer or on an emergency basis:</p> <ul type="disc" class="default-list"> <li>Managing threat detection and response.</li> <li>Providing threat prevention services.</li> <li>Conducting penetration tests and threat hunting.</li> <li>Assisting with media and PR management.</li> <li>Conducting root cause analysis.</li> <li>Conducting crisis management.</li> <li>Maintaining regulatory compliance.</li> </ul> <p><i>Get help deciding between deploying incident response in-house or employing a service provider, and read up on the </i><a href="https://www.techtarget.com/searchsecurity/feature/Top-10-incident-response-vendors"><i>leading incident response software, vendors and service providers</i></a><i>.</i></p> </section> <section class="section main-article-chapter" data-menu-title="Incident response and SOAR"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Incident response and SOAR</h2> <p><a href="https://www.techtarget.com/searchsecurity/definition/SOAR">SOAR</a> is a collection of technologies that, when combined, help security teams aggregate, analyze, detect and respond to security events with little or no human input. The main functions of each component of SOAR are outlined below:</p> <ul type="disc" class="default-list"> <li><b>Security orchestration. </b>This function connects and integrates internal and external tools through built-in or custom integrations and APIs. It collects and consolidates data from various tools to trigger response functions, based on defined incident analysis parameters and processes.</li> <li><b>Security automation.</b> This function uses the data collected during security orchestration to trigger workflows and tasks based on defined thresholds and actions outlined in incident response playbooks. SOAR platforms can automatically remediate lower-risk vulnerabilities and complete low-level tasks historically performed by human analysts, such as vulnerability scanning. High-risk threats also can automatically escalate to security analysts for further investigation.</li> <li><b>Security response.</b> Delivered via a single view, this function enables security, network and systems analysts to access and share threat intelligence, collaborate and conduct post-incident response activities.</li> </ul> <p>SIEM systems' operations are <a href="https://www.techtarget.com/searchsecurity/answer/SOAR-vs-SIEM-Whats-the-difference">similar to</a> those of SOAR platforms, but SIEMs focus primarily on detection and alerting, with limited automation capabilities.</p> <p>SOAR platforms <a href="https://www.techtarget.com/searchsecurity/tip/Top-6-SOAR-uses-cases-to-implement-in-enterprise-SOCs">augment human analysts</a> with threat intelligence coordination, case management, vulnerability management, automated enrichment for remediation, threat hunting and incident response automation. In these use cases, SOAR platforms help improve productivity; automate repetitive, tedious and low-importance tasks; use existing security tools better and more contextually; and improve third-party tool integration, among other benefits. SOAR platforms aren't without challenges, however. Namely, SOARs might not be able to integrate with all security tools easily or at all, do not address security culture within an organization and could fail to live up to inflated user expectations.</p> <p><i>Learn more about the </i><a href="https://www.techtarget.com/searchsecurity/feature/Top-benefits-of-SOAR-tools-plus-potential-pitfalls-to-consider"><i>benefits and challenges of SOAR systems</i></a><i>.</i></p> </section> <section class="section main-article-chapter" data-menu-title="Incident response: Don't wait for an attack to occur"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Incident response: Don't wait for an attack to occur</h2> <p>Incident response is a cornerstone of any enterprise cybersecurity program; its importance cannot be overstated. Quickly responding to security incidents effectively and efficiently helps minimize damage, improve recovery time, restore business operations and avoid high costs.</p> <p>But as Benjamin Franklin would attest, "Look before or you'll find yourself behind." In other words, prevention is key. A well-thought-out incident response plan and top-notch incident response team will prepare organizations for when the inevitable happens. But the first line of defense should always be keeping networks and data safe, as well as ensuring users are empowered and security-aware.</p> <p><i>Alissa Irei is senior site editor of TechTarget Security.</i></p> <p><i>Sharon Shea is executive editor of TechTarget Security.</i></p> </section> Incident response is an organized, strategic approach to detecting and managing cyberattacks in ways that minimize damage, recovery time and total costs. https://cdn.ttgtmedia.com/visuals/digdeeper/5.jpg https://www.techtarget.com/searchsecurity/definition/incident-response Wed, 10 Jun 2026 00:00:00 GMT What is incident response? A complete guide <p>DevOps is a software development approach that brings development and IT operations teams together to deliver applications faster and more reliably.</p> <p>The philosophy promotes better communication and collaboration between the two teams -- and others -- in an organization. It includes adopting iterative software development, automation and programmable infrastructure deployment and maintenance. <a href="https://www.techtarget.com/searchitoperations/tip/Target-tangible-IT-goals-during-a-DevOps-culture-shift">DevOps also includes cultural changes</a>, such as building trust and cohesion between developers and systems administrators and aligning technological projects to business requirements. DevOps can transform software delivery processes, job roles, tools and best practices.</p> <p>DevOps isn't a specific technology, but DevOps environments do use common methodologies:</p> <ul class="default-list"> <li>Continuous integration and continuous delivery (<a href="https://www.techtarget.com/searchsoftwarequality/CI-CD-pipelines-explained-Everything-you-need-to-know">CI/CD</a>) or continuous deployment tools, with an emphasis on task automation.</li> <li>Systems and tools that support DevOps adoption, including software development, real-time monitoring, incident management, resource provisioning, <a href="https://www.techtarget.com/searchitoperations/definition/configuration-management-CM">configuration management</a> and collaboration platforms.</li> <li>Cloud computing, microservices and containers implemented concurrently with DevOps methodologies.</li> </ul> <p>A DevOps approach is one of many techniques IT staff use to execute IT projects that meet business needs. DevOps doesn't have an official framework, but the CALMS framework (culture, automation, lean, measurement and sharing) is a popular implementation model.</p> <p>Some professionals believe that the simple combination of development and IT ops isn't enough, and that DevOps should include business (BizDevOps) and other areas. For example, DevSecOps, which is the integration of security into the DevOps lifecycle, is increasingly important in today's cybersecurity landscape.</p> <section class="section main-article-chapter" data-menu-title="Why is DevOps important?"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Why is DevOps important?</h2> <p>DevOps has been shown to improve software quality and development project outcomes for the enterprise. Such improvements take several forms:</p> <ul class="default-list"> <li><b>Development outcomes.</b> DevOps follows a cyclical, iterative development process. DevOps projects typically start small with minimal features, then systematically refine and add functionality throughout the project's lifecycle. This enables the business to be more responsive to changing markets, user demands and competitive pressures.</li> <li><b>Product quality.</b> The cyclical, iterative nature of DevOps ensures that products are tested continuously as existing defects are remediated and new issues are identified. Much of this is handled before each release, resulting in frequent releases that enable DevOps to deliver software with fewer bugs and better availability compared to software created with traditional paradigms.</li> <li><b>Deployment management.</b> DevOps integrates software development and IT ops tasks, often enabling developers to provision, deploy and manage each software release with little, if any, intervention from IT. This frees IT staff to focus on more strategic tasks. Deployment can take place on local infrastructure or in the public cloud, depending on the project's specific goals.</li> </ul> <p>A well-executed DevOps environment enables a business to deliver more competitive, higher-quality software products to market faster, with lower support and maintenance demands than traditional development approaches.</p> <h3>What are the benefits of DevOps?</h3> <p>DevOps benefits include the following:</p> <ul class="default-list"> <li>Faster time to market for software, enhancing revenue and competitive opportunities for the business.</li> <li>Rapid improvement based on user and stakeholder feedback.</li> <li>Better software quality, better deployment practices and less downtime from more frequent testing.</li> <li>Improvement to the entire software delivery pipeline through builds, repository use, validations and deployment.</li> <li>Less menial work across the DevOps pipeline, thanks to automation.</li> <li>Streamlined development processes through increased responsibility and code ownership in development.</li> <li>Broader roles and skills.</li> </ul> </section> <section class="section main-article-chapter" data-menu-title="How does DevOps work?"> <h2 class="section-title"><i class="icon" data-icon="1"></i>How does DevOps work?</h2> <p>DevOps is a methodology meant to improve work throughout the software development lifecycle (SDLC). You can <a href="https://www.techtarget.com/searchitoperations/tip/Demystify-the-DevOps-process-step-by-step">visualize a DevOps process</a> as an infinite loop, comprising these DevOps pipeline stages: plan, code, build, test, release, deploy, operate, monitor and -- through feedback -- plan, which resets the loop.</p> <div class="youtube-iframe-container"> <iframe id="ytplayer-0" src="https://www.youtube.com/embed/IY9WvL95azs?autoplay=0&modestbranding=1&rel=0&widget_referrer=null&enablejsapi=1&origin=https://www.techtarget.com" type="text/html" height="360" width="640" frameborder="0" loading="lazy"></iframe> </div> <p>Ideally, the cyclical loop that comprises each DevOps iteration alleviates significant stress on development outcomes.</p> <p>DevOps gives organizations far more flexibility in developing and releasing software that matures systematically over time, allowing teams to learn, adjust and experiment in ways that traditional development methods don't support.</p> <p>To align software with expectations, developers and stakeholders communicate about the project, and developers work on small updates that go live independently of one another.</p> <p>To avoid wait times, IT teams use CI/CD pipelines and other automation to move code from one step of development and deployment to another. Teams review changes immediately and can rely on policies and tools to enforce policies and ensure releases meet standards.</p> <p>To deploy good code to production, DevOps adherents use containers or other methods to ensure the software behaves consistently from development through testing and into production. They deploy changes individually so that problems are traceable. Teams rely on automation and configuration management for consistent deployment and hosting environments. Problems they discover in live operations lead to code improvements, often through a blameless post-mortem investigation and continuous feedback channels.</p> <p>Developers might support the live software, which puts the onus on them to address runtime considerations. IT ops administrators might be involved in the software design meetings, offering guidance on how to use resources efficiently and securely. Anyone can contribute to blameless post-mortems.</p> <h3>Building a DevOps culture</h3> <p>The core pillars of DevOps culture are collaboration, shared ownership and accountability, automation, and learning and continuous improvement. Each of these pillars plays a vital role in realizing the full benefits of DevOps and quickly delivering reliable software at scale.</p> <p>Although there's no one way to establish a DevOps culture, here are some best practices to consider:</p> <ul class="default-list"> <li>Change the organizational structure.</li> <li>Integrate DevOps culture into hiring.</li> <li>Adopt blameless principles.</li> <li>Provide learning opportunities.</li> <li>Communicate clearly about automation.</li> <li>Seek feedback.</li> <li>Measure the effectiveness of DevOps culture.</li> </ul> <p>Leaders should model core values, set clear expectations without micromanaging and offer incentives to teams that meet DevOps metrics.</p> </section> <section class="section main-article-chapter" data-menu-title="DevOps methodologies, principles and strategies"> <h2 class="section-title"><i class="icon" data-icon="1"></i>DevOps methodologies, principles and strategies</h2> <p><b>Code repositories.</b> Version-controlled source code repositories enable multiple developers to work on code. Developers check code out and in and can revert to a previous version if needed. These tools keep a record of modifications made to the source code -- including who made the changes and when. Without tracking, developers might struggle to follow which changes are recent and which versions of the code are available to end users.</p> <p>In a CI/CD pipeline, a code change committed in the version-control repository automatically triggers the next steps, such as a static code analysis or build and unit tests.</p> <p><b>CI/CD pipeline engines.</b> CI/CD enables DevOps teams to frequently validate and deliver applications to end users through automation during the development lifecycle. The continuous integration tool automates processes so developers can create, test and validate code in a shared repository as often as needed without manual effort. Continuous delivery extends these automated steps into production-level tests and release management configurations. Continuous deployment goes a step further, invoking tests, configuration and provisioning, and providing monitoring and potential rollback capabilities.</p> <p><b>Artifact repositories.</b> Source code is compiled into an artifact for testing. Artifact repositories enable version-controlled, object-based outputs. Artifact management is a good practice for the same reasons as version-controlled source code management.</p> <p><b>Configuration management and IaC.</b> Configuration management systems enable IT to provision and configure software, middleware and infrastructure using scripts or templates. The DevOps team can set up deployment environments for software code releases and enforce policies on servers, containers and VMs through a configuration management tool. Changes to the deployment environment can be version-controlled and tested, enabling DevOps teams to manage infrastructure as code (<a href="https://www.techtarget.com/searchitoperations/definition/Infrastructure-as-Code-IAC">IaC</a>).</p> <figure class="main-article-image full-col" data-img-fullsize="https://www.techtarget.com/rms/onlineimages/itops-devops_dissected-f.png"> <img data-src="https://www.techtarget.com/rms/onlineimages/itops-devops_dissected-f_mobile.png" class="lazy" data-srcset="https://www.techtarget.com/rms/onlineimages/itops-devops_dissected-f_mobile.png 960w,https://www.techtarget.com/rms/onlineimages/itops-devops_dissected-f.png 1280w" alt="Table listing components of a DevOps methodology, with a description and benefits of each." height="616" width="560"> <figcaption> <i class="icon pictures" data-icon="z"></i>From automated code preparation to CI/CD pipelines, orchestration, monitoring and feedback, here's how every piece contributes to a successful DevOps methodology. </figcaption> <div class="main-article-image-enlarge"> <i class="icon" data-icon="w"></i> </div> </figure> <p><b>Containers.</b> Containers are isolated runtimes for software on a shared OS. Containers provide abstraction that enables code to work the same way across different underlying infrastructures from development to testing and staging, and then to production.</p> <p><b>GitOps.</b> GitOps espouses declarative source control over application and infrastructure code. Everything about the software, from feature requirements to the deployment environment, comes from a single source of truth. <a href="https://www.techtarget.com/searchitoperations/tip/Compare-GitOps-vs-DevOps-for-modern-app-deployments">GitOps is associated with change management</a> and deployment techniques, such as immutable infrastructure, which dictates replacing or reinstancing -- rather than upgrading or changing -- deployed code each time a change is made.</p> <p><b>Cloud environments.</b> DevOps organizations often concurrently adopt cloud infrastructure because they can automate its deployment, scaling and other management tasks. Many cloud vendors also offer CI/CD services.</p> <p><b>Cloud-based DevOps pipelines.</b> Public cloud providers offer native DevOps tool sets for use with workloads on their platforms. Cloud adopters can use pre-integrated services or run third-party tools.</p> <p><b>As-a-service models.</b> <a href="https://www.techtarget.com/searchitoperations/definition/DevOps-as-a-service-DaaS">DevOps as a service</a> is a delivery model for a set of tools that facilitates collaboration between an organization's software development and IT ops teams. In this delivery model, the provider assembles a suite of tools and handles the integrations to seamlessly cover the overall process of code creation, delivery and maintenance.</p> <p>In other cases, service providers act as consultants, assisting businesses with DevOps projects or supplementing expertise that might be lacking across the DevOps process. Service providers should be evaluated based on factors including time in business, proven experience -- particularly in related market verticals -- and compatibility with existing DevOps tools and practices.</p> <p><b>Monitoring and observability.</b> Monitoring and observability tools enable DevOps professionals to oversee the performance and security of code releases on systems, networks and infrastructure. They can combine monitoring with analytics tools that provide operational intelligence. DevOps teams use these tools together to analyze how code changes affect the overall environment. Observability specifically uses metrics, logs and traces to understand why something is happening.</p> <p><b>DevOps vs. Agile vs. Waterfall.</b> In terms of strategy, <a href="https://www.techtarget.com/searchsoftwarequality/opinion/DevOps-vs-waterfall-Can-they-coexist">DevOps is associated with Agile</a> software development because Agile practitioners promoted DevOps as a way to extend the methodology into production. This mindset has even been labeled a counterculture to the IT service management practices championed in ITIL. In traditional Waterfall development, teams used an all-or-nothing approach, gathering requirements upfront and then writing, testing and releasing code as events. They addressed any performance or reliability issues as an afterthought.</p> <figure class="main-article-image full-col" data-img-fullsize="https://www.techtarget.com/rms/onlineImages/dev_ops-evangelist.jpg"> <img data-src="https://www.techtarget.com/rms/onlineImages/dev_ops-evangelist_mobile.jpg" class="lazy" data-srcset="https://www.techtarget.com/rms/onlineImages/dev_ops-evangelist_mobile.jpg 960w,https://www.techtarget.com/rms/onlineImages/dev_ops-evangelist.jpg 1280w" alt="Graphic showing how to be a DevOps evangelist. " height="413" width="559"> <figcaption> <i class="icon pictures" data-icon="z"></i>These benefits show how DevOps enhances IT organizations even if they have already adopted Agile. </figcaption> <div class="main-article-image-enlarge"> <i class="icon" data-icon="w"></i> </div> </figure> <p>To refine their practices, organizations should understand the related contexts of DevOps, Agile and Waterfall development, site reliability engineering (SRE) and SysOps, and even the variations within DevOps. These approaches influence how organizations structure teams and define responsibilities.</p> </section> <section class="section main-article-chapter" data-menu-title="DevOps skills and job roles"> <h2 class="section-title"><i class="icon" data-icon="1"></i>DevOps skills and job roles</h2> <p>Depending on the type of organization, there are <a href="https://www.techtarget.com/searchitoperations/feature/Know-the-key-DevOps-roles-and-responsibilities-for-team-success">several DevOps roles</a> that IT leaders should consider for the team, as they each bring valuable skills to the table. The job descriptions vary, and not all are needed due to overlapping responsibilities, but here's a basic overview of the different types of roles:</p> <ul class="default-list"> <li><b>Software developers.</b> These team members write, update and fix application code. Ideal candidates have experience with several programming languages and app development methodologies. They should also be familiar with production environments.</li> <li><b>IT operations engineers.</b> Engineers in this role provision and deploy host infrastructure and software releases. They also monitor software in production. Beyond having IT ops experience, people in this role should understand the SDLC and be able to write application code and sysadmin scripts.</li> <li><b>DevOps engineers.</b> Tasked with building and managing CI/CD pipelines and automations, <a href="https://www.techtarget.com/searchitoperations/definition/DevOps-engineer">DevOps engineers</a> should know infrastructure design principles and be familiar with multiple platforms. They should have expertise in automation coding.</li> <li><b>Systems architects.</b> This role evaluates services for hosting DevOps tools, oversees DevOps tool consolidation and monitors CI/CD pipelines. Ideal candidates should specialize in DevOps tools and high-level infrastructure design. Some organizations combine the DevOps engineer and systems architect roles because of their similarities.</li> <li><b>QA engineers.</b> These engineers run manual tests, write automated tests for software releases and address any bugs. Necessary skills include writing quick, comprehensive tests and knowledge of test automation frameworks.</li> <li><b>UX engineers.</b> This role involves working with developers and users to ensure the software and UI meet their needs. Effective communication and collaboration are key.</li> <li><b>Security engineers.</b> Security engineers test application security and coordinate with developers and IT engineers to develop secure applications and infrastructure. Familiarity with and experience in DevSecOps is increasingly important.</li> </ul> <figure class="main-article-image full-col" data-img-fullsize="https://www.techtarget.com/rms/onlineimages/itops-developer_responsibilities_devsecops-f.png"> <img data-src="https://www.techtarget.com/rms/onlineimages/itops-developer_responsibilities_devsecops-f_mobile.png" class="lazy" data-srcset="https://www.techtarget.com/rms/onlineimages/itops-developer_responsibilities_devsecops-f_mobile.png 960w,https://www.techtarget.com/rms/onlineimages/itops-developer_responsibilities_devsecops-f.png 1280w" alt="Chart listing four developer responsibilities in a DevSecOps model, with an illustration of how it fits in the DevOps workflow. " height="324" width="560"> <figcaption> <i class="icon pictures" data-icon="z"></i>For developers, a DevSecOps role integrates security across the DevOps pipeline, from code analysis to automated testing to threat modeling. </figcaption> <div class="main-article-image-enlarge"> <i class="icon" data-icon="w"></i> </div> </figure> <ul class="default-list"> <li><b>DevOps evangelists.</b> Team members in this role help build a strong DevOps culture in the organization. This can be a separate role or someone already on the team. They should be able to convey the importance of DevOps to decision-makers.</li> <li><b>SREs.</b> These engineers work with developers and IT engineers on application and infrastructure design, monitor production environments and mitigate incidents. Responsibilities might overlap with IT and QA engineers, but SREs typically do a lot of code-based automation.</li> <li><b>Cloud engineers.</b> This role involves deploying and managing applications in the cloud and overseeing any multi-cloud strategies. Expertise in cloud environments and tools can set them apart from general IT engineers.</li> <li><b>Automation engineers.</b> Tasked with implementing and troubleshooting automated workflows, automation engineers sometimes have a broad role that encompasses DevOps processes and other business workflows. They should have experience with emerging technologies.</li> <li><b>AI DevOps engineers.</b> These engineers oversee the use of AI in DevOps and CI/CD pipelines. Other roles could cover this, but as AI adoption increases, it might be worth creating a dedicated role for the compliance and security implications.</li> </ul> <p>IT leaders can establish DevOps roles in one of three ways:</p> <ol class="default-list"> <li>Replace separate development and IT ops departments with a combined DevOps department.</li> <li>Run DevOps as a separate team alongside existing development and IT ops teams.</li> <li>Embed DevOps engineers into each department.</li> </ol> <p>In addition to business acumen, DevOps team members should have a <a href="https://www.techtarget.com/searchitoperations/tip/DevOps-engineer-skills-needed-for-continuous-deployment">variety of skills</a> in software development, infrastructure management and project management.</p> <p>More specifically, DevOps engineers should be familiar with various platforms, programming and scripting languages, configuration management, version management, IaC, provisioning, deployment, security, tracking and assessing release performance, network optimization, troubleshooting, integration, communication and team management.</p> <p>There are many <a href="https://www.techtarget.com/whatis/feature/9-best-free-DevOps-certifications-and-training-courses">DevOps certifications and training courses</a> available, including, but not limited to, the following:</p> <ul class="default-list"> <li>DevOps Foundation Exam Study Guide.</li> <li>DevOps Culture and Mindset.</li> <li>Introduction to DevOps and Site Reliability Engineering.</li> <li>Kubernetes: Getting Started.</li> <li>Docker Essentials.</li> <li>Getting Started with DevOps on AWS.</li> <li>Preparing for Google Cloud Certification: Cloud DevOps Engineer Professional Certificate.</li> <li>Microsoft Certified: DevOps Engineer Expert.</li> <li>Red Hat's Developing Cloud-Native Apps with Microservices Architectures.</li> <li>IBM's Introduction to DevOps.</li> </ul> </section> <section class="section main-article-chapter" data-menu-title="DevOps adoption best practices"> <h2 class="section-title"><i class="icon" data-icon="1"></i>DevOps adoption best practices</h2> <p>The adoption of DevOps or other CD paradigms can be disruptive to software and management teams. There are inevitable changes to workflows, processes, tool sets and even staffing that will drive the need for more training. DevOps adoption can easily get off track and eventually fall by the wayside. Below are some tips to help ease DevOps adoption and increase the chances of DevOps success.</p> <h3>Start small</h3> <p>DevOps transformations don't happen overnight. Many companies start with a pilot project -- a simple application where they can get a feel for new practices and tools. DevOps teams look for quick, easy wins to refine workflows, learn the tools and prove the value of DevOps principles. For large-scale DevOps adoption, try moving in stages.</p> <h3>Consider the workflows</h3> <p>Initially, DevOps can mean a commitment from development and IT ops teams to understand the concerns and technical constraints at each stage of the software project. Agree upon KPIs to improve, such as shorter cycle times or fewer bugs in production. Understand how DevOps practices map to current development and deployment practices and plan suitable workflow changes to enhance software quality, security and compliance. Lay the groundwork for continuous processes by communicating across job roles.</p> <h3>Select the proper tools</h3> <p>Evaluate the existing tools for software development and IT operations. More or different tools might be needed. Identify process shortcomings, such as a step that's always handled manually -- for example, moving from a code commit to testing -- or a tool without APIs to connect with other tools.</p> <figure class="main-article-image full-col" data-img-fullsize="https://www.techtarget.com/rms/onlineImages/itops-devops_toolchain.png"> <img data-src="https://www.techtarget.com/rms/onlineImages/itops-devops_toolchain_mobile.png" class="lazy" data-srcset="https://www.techtarget.com/rms/onlineImages/itops-devops_toolchain_mobile.png 960w,https://www.techtarget.com/rms/onlineImages/itops-devops_toolchain.png 1280w" alt="Chart showing links in the DevOps toolchain. " height="230" width="560"> <figcaption> <i class="icon pictures" data-icon="z"></i>Make sure your DevOps toolchain supports the flow of work from application development through testing and deployment. </figcaption> <div class="main-article-image-enlarge"> <i class="icon" data-icon="w"></i> </div> </figure> <p>Consider standardizing on a single DevOps pipeline across the whole company. With one pipeline, team members can move from one project to another without reskilling. This enables security specialists to harden the pipeline and eases license management. The tradeoff is that DevOps teams give up the freedom to use what works best for them.</p> <h3>Employ meaningful metrics</h3> <p>Simply adopting DevOps isn't enough to ensure success. Understand the need for DevOps in the first place -- what problems it is intended to solve, or what benefits it is intended to deliver. <a href="https://www.techtarget.com/searchitoperations/tip/Nine-DevOps-metrics-you-should-use-to-gauge-improvement">Select metrics and KPIs</a> that will show those outcomes and then plan to measure and report on those metrics as an objective gauge of DevOps success.</p> <p>Specific metrics will vary across organizations, but leaders should incorporate a mix of delivery and deployment, reliability and stability, operational efficiency, and business and customer impact KPIs.</p> <p>Start with the five DORA metrics, an industry-standard benchmark for delivery and reliability established by Google Cloud's DevOps Research and Assessment team:</p> <ol class="default-list"> <li>Deployment frequency.</li> <li>Mean lead time for changes.</li> <li>Mean time to recover.</li> <li>Change failure rate.</li> <li>Reliability.</li> </ol> <h3>Use the DevOps maturity model</h3> <p>The DevOps maturity model illustrates five principal phases of adoption, ranging from novice to well-established. Organizations can use the DevOps maturity model as a guide to adoption by identifying their place in the model:</p> <ul class="default-list"> <li><b>Initial.</b> Teams are siloed; work is reactive and done with ad hoc tool and process choices.</li> <li><b>Defined.</b> A pilot project is a proof of concept that defines a DevOps approach, basic processes and tools.</li> <li><b>Managed.</b> The organization scales up DevOps adoption with lessons learned from the pilot. The pilot's results are repeatable with different staff members and project types.</li> <li><b>Measured.</b> With processes and tools in place, the teams share knowledge and refine practices. Automation and tool connectivity increase, and standards are enforced through policies.</li> <li><b>Optimized.</b> Continuous improvement occurs. DevOps might evolve into different tool sets or processes to fit use cases. For example, customer-facing apps have a higher release frequency, and financial management apps <a href="https://www.techtarget.com/searchitoperations/feature/5-DevSecOps-best-practices-to-prioritize">follow DevSecOps best practices</a>: <ul class="default-list"> <li>Embedding security early with a "shift left" approach.</li> <li>Mapping DevSecOps to compliance frameworks.</li> <li>Integrating IaC security.</li> <li>Automating security across the pipeline.</li> <li>Fostering cross-functional ownership.</li> <li>Standardizing and securing toolchains.</li> <li>Securing the software supply chain.</li> <li>Implementing secrets management and identity controls.</li> <li>Implementing continuous monitoring and feedback.</li> <li>Adopting policy-as-code governance.</li> <li>Establishing security champion programs.</li> </ul> </li> </ul> </section> <section class="section main-article-chapter" data-menu-title="What are the challenges of DevOps?"> <h2 class="section-title"><i class="icon" data-icon="1"></i>What are the challenges of DevOps?</h2> <p>The DevOps paradigm introduces <a target="_blank" href="https://www.invensislearning.com/blog/devops-implementation-challenges-solutions/" rel="noopener">complexities</a> and changes that can be difficult to implement and manage within a busy organization. Common DevOps challenges include the following:</p> <ul class="default-list"> <li>Organizational and IT departmental changes, including new skills and job roles, which can be disruptive to development teams and the business.</li> <li>Expensive tools and platforms, including training and support to use them effectively.</li> <li>Development and IT tool proliferation.</li> <li>Unnecessary, fragile, poorly implemented and maintained or unsafe automation.</li> <li>Logistics and workload difficulties scaling DevOps across multiple projects and teams.</li> <li>Riskier deployment due to a fail-fast mentality and job generalization vs. specialization, where access to production systems is handled by less IT-savvy personnel.</li> <li>Regulatory compliance, especially when role separation is required.</li> <li>New bottlenecks, such as automated testing or repository utilization.</li> </ul> <p>In short, DevOps doesn't solve every business problem or benefit every software development project in the same way.</p> </section> <section class="section main-article-chapter" data-menu-title="DevOps tools"> <h2 class="section-title"><i class="icon" data-icon="1"></i>DevOps tools</h2> <p>DevOps is a mindset, not a tool set. But it's hard to do anything in an IT team without suitable and well-integrated tools. In general, DevOps practitioners rely on CI/CD pipelines, containers and cloud hosting. Tools can be open source, proprietary or supported distributions of open source technology.</p> <p>Here are some examples of the different types of tools available:</p> <ul class="default-list"> <li><b>Artifact repositories.</b> AWS CodeArtifact, Azure Artifacts, Cloudsmith, JFrog Artifactory, Packagecloud, ProGet and Sonatype Nexus Repository.</li> <li><b>CI/CD pipeline engines.</b> Azure Pipelines, CircleCI, Jenkins, GitHub Actions and GitLab CI/CD.</li> <li><b>Cloud-based DevOps pipelines.</b> AWS CloudFormation and CodePipeline, and Azure DevOps and Pipelines.</li> <li><b>Cloud environments.</b> AWS, Google Cloud and Microsoft Azure.</li> <li><b>Code repositories.</b> Bitbucket, Git, GitHub and GitLab.</li> <li><b>Configuration management and IaC.</b> Ansible, Chef, Puppet and SaltStack. IaC-specific tools include AWS CloudFormation and HashiCorp Terraform.</li> <li><b>Containers. </b>Amazon Elastic Kubernetes Service, Docker, Kubernetes, Microsoft (Windows-specific container options) and Red Hat.</li> <li><b>GitOps.</b> Argo CD and Flux CD.</li> <li><b>Monitoring and observability.</b> Amazon CloudWatch, Datadog, Dynatrace, Grafana, New Relic, OpenTelemetry, Prometheus, and Splunk.</li> </ul> </section> <section class="section main-article-chapter" data-menu-title="The evolution of DevOps"> <h2 class="section-title"><i class="icon" data-icon="1"></i>The evolution of DevOps</h2> <p>As DevOps became popular, organizations formalized DevOps approaches. Retailer Target originated the DevOps Dojo training method, for example. Vendors touted DevOps-enabling capabilities in tools, from collaboration chatbots to CI/CD suites built into cloud services.</p> <p>Technologies such as microservices, virtual containers and public cloud services offered a natural fit for the fast, flexible nature of DevOps.</p> <h3>Modern trends in DevOps</h3> <p>DevOps continues to evolve, as AI surfaces to aid in everything from code creation to incident management. <a href="https://www.techtarget.com/searchitoperations/tip/What-to-expect-as-AI-for-DevOps-advances-in-the-enterprise">AI for DevOps</a> means smarter automation, even shorter wait times and seamless translation of business needs into technology offerings.</p> <p>The role of AI in DevOps practices affects teams in other ways as well. Established processes and DevOps roles and responsibilities are evolving as automation use in the SDLC increases. The tools that DevOps teams use are also getting smarter, ultimately leading to tool consolidation.</p> <p>Other key <a href="https://www.techtarget.com/searchitoperations/feature/Top-DevOps-trends-to-watch">DevOps trends in 2026</a> include platform teams joining DevOps teams and the use of intent-driven infrastructure, which enables teams to think less about the environment in which their software will be deployed, as AI determines the best fit based on workload analysis.</p> <p>In addition, organizations are encouraging DevOps teams to be even more cost-conscious amid higher overall cloud spending. Organizations are also asking that regulatory concerns and recent geopolitical issues be at the forefront of DevOps teams' minds when developing and deploying software.</p> <p>Currently, DevOps teams are building and customizing software to incorporate AI and automation, while the future of DevOps sees teams focusing more on high-level business issues and less on the tasks that AI and automation can handle.</p> <p><i>Stephen J. Bigelow, senior technology editor at TechTarget, has more than 20 years of technical writing experience in the PC and technology industry.</i></p> <p><i>Ryann Burnett, executive managing editor, has 10 years of experience at TechTarget Editorial, covering virtualization, containers, monitoring, observability, data centers, server hardware, IoT and other technologies.</i></p> <p><i>Meredith Courtemanche and Alexander S. Gillis also contributed to this article.</i></p> </section> DevOps is a software development approach that brings development and IT operations teams together to deliver applications faster and more reliably. https://cdn.ttgtmedia.com/visuals/digdeeper/4.jpg https://www.techtarget.com/searchitoperations/definition/DevOps Tue, 28 Apr 2026 09:17:00 GMT What is DevOps? Meaning, methodology and guide <p>A human resources information system (HRIS) is software that aids organizations in maintaining detailed employee information and managing and automating core human resources (<a href="https://www.techtarget.com/searchhrsoftware/definition/core-HR-core-human-resources">core HR</a>) processes.</p> <p>An HRIS can help improve organizational security, compliance and employee experience. CHROs whose organizations are considering getting an HRIS for the first time should learn about the technology to ensure that their company’s new HRIS meets the organization’s needs. CHROs whose companies are currently using an HRIS should learn about the latest HRIS trends to confirm whether their current HRIS is still the right fit for their company.</p> <section class="section main-article-chapter" data-menu-title="HRIS as an employee database"> <h2 class="section-title"><i class="icon" data-icon="1"></i>HRIS as an employee database</h2> <p>An HRIS provides a centralized repository of employee primary data that the human resources management (<a href="https://www.techtarget.com/searchhrsoftware/definition/human-resource-management-HRM">HRM</a>) team needs to complete core HR tasks.</p> <p>HRIS software stores, processes and manages employee data, including the following:</p> <ul class="default-list"> <li>Names.</li> <li>Addresses.</li> <li>National IDs (non-U.S.) or Social Security numbers.</li> <li>Date of hire.</li> <li>Visa or work permit information (in the case of international hires).</li> <li>Compensation.</li> <li>Benefits selected (health insurance, dental, vision, etc.).</li> <li>Information about dependents.</li> </ul> <p>Some HRIS platforms also store information such as time and attendance, job history, training and development, and performance reviews.</p> <p>HRIS software typically also provides HR functions, such as <a href="https://www.techtarget.com/searchhrsoftware/definition/recruiter">recruiting</a>, applicant tracking, time and attendance management, performance appraisals and <a href="https://www.techtarget.com/searchhrsoftware/definition/benefits-administration">benefits administration</a>. An HRIS can also offer <a href="https://www.techtarget.com/searchhrsoftware/definition/employee-self-service">employee self-service</a> and accounting functions.</p> </section> <section class="section main-article-chapter" data-menu-title="HRIS functions"> <h2 class="section-title"><i class="icon" data-icon="1"></i>HRIS functions</h2> <p>As an HR tool, an HRIS usually features modules to handle the following tasks:</p> <ul class="default-list"> <li>Core HR.</li> <li><a href="https://www.techtarget.com/searchdatamanagement/definition/master-data-management">Primary data management</a>.</li> <li>Organizational management, such as positions and departments.</li> <li>Employee and manager self-services.</li> <li>Absence and leave management.</li> <li>Benefits administration.</li> <li><a href="https://www.techtarget.com/searchcio/definition/workflow">Workflows</a>.</li> <li>Performance management.</li> <li>Recruiting and applicant tracking.</li> <li><a href="https://www.techtarget.com/searchhrsoftware/definition/compensation-management">Compensation management</a>.</li> <li>Training tracking that may complement a learning management system (<a href="https://www.techtarget.com/searchcio/definition/learning-management-system">LMS</a>) and organizational development.</li> <li>Reporting and basic analytics.</li> <li><a href="https://www.techtarget.com/searchhrsoftware/definition/payroll-software">Payroll</a>.</li> <li><a href="https://www.techtarget.com/searchhrsoftware/definition/employee-onboarding-and-offboarding">Onboarding</a>.</li> </ul> <p>HRIS provides a comprehensive set of functionalities to serve most HR needs. Without an HRIS, data might be stored in unsecured or paper-based documents or <a href="https://www.techtarget.com/whatis/definition/spreadsheet">spreadsheets</a>. Manual data entry can cause errors, and manual cross-checking of documents and spreadsheets can be time-consuming and often confusing, especially with a lack of standardization on how data is captured and stored.</p> <p>Even when a specific system is purchased to cover a process -- such as benefits administration -- it might require manually entering employee data changes to keep the system up to date. If multiple systems are used, data reentry could be required for each system, or users might need to export data from one system, change it and then import it into another system.</p> <p>In some instances, payroll might be part of an HRIS. However, many vendors either don't include payroll as part of their HRIS offering or -- as with companies such as <a href="https://www.techtarget.com/searchoracle/definition/Oracle">Oracle</a>, <a href="https://www.techtarget.com/searchhrsoftware/definition/Workday">Workday</a> and <a href="https://www.techtarget.com/searchsap/definition/SAP-SuccessFactors">SAP SuccessFactors</a> -- they sell payroll as a separate system that integrates with their HRIS.</p> <figure class="main-article-image full-col" data-img-fullsize="https://www.techtarget.com/rms/onlineImages/fin_apps-human_resource_information_system.jpg"> <img data-src="https://www.techtarget.com/rms/onlineImages/fin_apps-human_resource_information_system_mobile.jpg" class="lazy" data-srcset="https://www.techtarget.com/rms/onlineImages/fin_apps-human_resource_information_system_mobile.jpg 960w,https://www.techtarget.com/rms/onlineImages/fin_apps-human_resource_information_system.jpg 1280w" alt="Functions of an HRIS diagram." height="335" width="558"> <figcaption> <i class="icon pictures" data-icon="z"></i>Human resources information systems comprise a wide range of functions that address all personnel and compensation issues. </figcaption> <div class="main-article-image-enlarge"> <i class="icon" data-icon="w"></i> </div> </figure> </section> <section class="section main-article-chapter" data-menu-title="The importance of HRIS"> <h2 class="section-title"><i class="icon" data-icon="1"></i>The importance of HRIS</h2> <p>HRIS is important to organizations and HR departments because it efficiently maintains and manages detailed employee information. In some ways, an HRIS can be considered a "smart" employee information <a href="https://www.techtarget.com/searchdatamanagement/definition/database">database</a>. The interaction of the data, the processes that can be performed, and the reporting capabilities make the data stored in the system more accessible and usable. This data enables HR teams to maintain accurate employee records and to generate useful reports that could inform HR and organizational decision-making.</p> <p>The information stored in the HRIS also facilitates seamless and efficient interactions between organizations and their employees, thus helping to create a more employee-friendly culture.</p> <p>HRIS with self-service functionality enables employees to take responsibility for their own information. They can independently access or update the information as needed, without involving or waiting for HR personnel. For example, they can check their benefits or leave accrual, or update their contact details on their own. This not only provides convenience for employees but also simplifies information management for HR teams.</p> <p>HRIS information also enables companies to better <i>know</i> their employees. Companies can use the knowledge and insights generated by the HRIS to connect with employees in meaningful and personalized ways to help workers discover the right training programs, devise <a href="https://www.techtarget.com/searchhrsoftware/tip/Top-professional-development-platforms">career development</a> plans and identify areas for improvement in their workplace performance.</p> <p>Through <a href="https://www.techtarget.com/whatis/definition/digitization">digitization</a> and automation, HRIS eliminates -- or reduces -- the need for paper-based and manual HR processes. It provides a centralized repository to maintain and update HR policies and procedures, enabling HR departments to automate, streamline and standardize many HR admin tasks, minimizing the potential for delays in processing requests and inaccuracies.</p> <p>A related benefit of HRIS is that it reduces the administrative burden for HR staff. By automating and streamlining many standard HR processes, the HRIS allows the staff to focus on performing more strategic and high-value work where their uniquely human skills can be applied best.</p> <p>HRIS also facilitates accurate record-keeping and reporting. These reports facilitate more informed, data-driven decision-making and enhance operational consistency and org-wide accountability.</p> <p>HRIS can also play a critical role in enabling <a href="https://www.techtarget.com/searchdatamanagement/definition/compliance">compliance</a>. For example, regulatory data, such as U.S. equal employment opportunity information or U.K. Working Time opt-out, can be stored, allowing organizations to gain insight into the workforce.</p> <p>HRIS can serve a critical role in enabling other HR systems to access employee data. Systems such as payroll and learning management systems require this data to offer HR services to employees. The HRIS facilitates this access by integrating with these systems. Integrating HRIS with other applications also creates greater HR efficiencies and reduces the need for data entry into multiple systems, thus minimizing the potential for costly errors that might hamper <a href="https://www.techtarget.com/searchhrsoftware/definition/employee-engagement">employee engagement</a>.</p> <figure class="main-article-image full-col" data-img-fullsize="https://www.techtarget.com/rms/onlineimages/hr_automation_benefits_and_challenges-f.png"> <img data-src="https://www.techtarget.com/rms/onlineimages/hr_automation_benefits_and_challenges-f_mobile.png" class="lazy" data-srcset="https://www.techtarget.com/rms/onlineimages/hr_automation_benefits_and_challenges-f_mobile.png 960w,https://www.techtarget.com/rms/onlineimages/hr_automation_benefits_and_challenges-f.png 1280w" alt="HR automation benefits and challenges graphic." height="246" width="559"> <figcaption> <i class="icon pictures" data-icon="z"></i>While the benefits of HR automation are substantial, it's important to note that there are some challenges to implementing these systems. </figcaption> <div class="main-article-image-enlarge"> <i class="icon" data-icon="w"></i> </div> </figure> </section> <section class="section main-article-chapter" data-menu-title="HRIS benefits"> <h2 class="section-title"><i class="icon" data-icon="1"></i>HRIS benefits</h2> <p>HRIS software can breathe new life into a company's HR processes and procedures. While the benefits vary depending on the system a company opts for or the modules it chooses, the following are <a href="https://www.techtarget.com/searchhrsoftware/tip/15-must-have-HR-software-features-and-system-requirements">key benefits of HRIS software</a>:</p> <ul class="default-list"> <li><b>Expedites tasks.</b> An HRIS enables the HR department to spend less time on time-consuming, repetitive or tedious administrative tasks, helps ensure the accuracy of employee data and makes it easier for employees to manage their information.</li> <li><b>Reduces paperwork.</b> Having a centralized repository for employee data removes the need to store paper files, reduces physical storage requirements, and makes searching for and finding information much easier. Digitization also reduces the costs involved in purchasing and managing physical materials like paper, file folders and cabinets.</li> <li><b>Simplifies predictive analysis and visualizations.</b> Most HRIS software can generate various reports, provide ad hoc reporting capabilities and offer <a href="https://www.techtarget.com/searchhrsoftware/definition/human-resources-analytics-talent-analytics">HR analytics</a> on important metrics such as head count and turnover. Modern HRIS software also offers <a href="https://www.techtarget.com/searchbusinessanalytics/definition/data-visualization">data visualization</a> capabilities for employee information, such as automatically rendering organizational charts or <a href="https://www.techtarget.com/searchcio/definition/managerial-grid-model-The-Blake-and-Mouton-Managerial-Grid-model">nine-box grid</a> employee assessment tools. CHROs and senior management can use these reports and visualizations to gain actionable insights into the workforce and take appropriate actions to address gaps.</li> <li><b>Empowers employees. </b>Employees can directly access and make changes to their personal information without contacting HR.</li> <li><b>Improves productivity.</b> Self-service features simplify the process of making changes to employee primary data or organizational data, making it less time-consuming than paper-based requests. Approval workflows enable changes to be approved or rejected, with the necessary individuals automatically notified. An HRIS might also offer mobile capabilities that extend self-service and provide additional flexibility for remote workers.</li> <li><b>Maintains compliance. </b>HR tasks are highly regulated, and there's little margin for error, particularly from a <a href="https://www.techtarget.com/searchcio/definition/regulatory-compliance">regulatory compliance</a> perspective. Many HRIS programs have monitoring capabilities and are designed with specific compliance regulations in mind. The most reliable HRIS products also automatically keep track of changing regulations. This helps organizations to stay compliant and avoid the negative consequences of non-compliance, such as legal issues, penalties, financial losses and reputational damage.</li> <li><b>Offers security and privacy.</b> <a href="https://www.techtarget.com/searchsecurity/Data-security-guide-Everything-you-need-to-know">Data security</a> and privacy are important factors when handling sensitive personal information. When using paper forms or spreadsheets, information can easily be accessed by people who aren't authorized. This can result in serious <a href="https://www.techtarget.com/searchsecurity/definition/data-breach">data breaches</a> and associated problems like reputational damage or regulatory fines. An HRIS includes multilayered security and privacy controls to secure employee data and keep it private.</li> <li><b>Provides scalability.</b> A <a href="https://www.techtarget.com/searchcloudcomputing/definition/cloud-application">cloud-based</a> HRIS is easily scalable depending on an organization's needs. As a company grows, the HRIS can be scaled up or down so it can continue to provide the benefits of employee data management and core HR standardization with minimal disruption to HR workflows.</li> <li><b>Offers data-driven features to support organizational decision-making.</b> Some HRIS software includes features such as <a href="https://www.techtarget.com/searchbusinessanalytics/definition/predictive-analytics">predictive analytics</a>, forecasting and modeling, which can aid HR and company leadership in making informed decisions based on actual data. They can also create forecasts and models about future staffing needs to better prepare for changes and ensure that a talent pipeline is in place to help the organization meet its goals and objectives.</li> </ul> </section> <section class="section main-article-chapter" data-menu-title="HRIS challenges"> <h2 class="section-title"><i class="icon" data-icon="1"></i>HRIS challenges</h2> <p>Well-designed HRIS software can bring many benefits to organizations and their HR functions. However, it also presents some challenges. Organizations need to be aware of these challenges to make the best use of the HRIS they implement. Some of the challenges include the following:</p> <ul class="default-list"> <li><b>Selection difficulties.</b> Some companies can struggle to select the "right" HRIS. To help with selection decisions, it's important to first analyze the organization's needs, pain points and challenges that the HRIS is expected to address or ameliorate. It's also important to ensure that the product aligns with the business goals by not getting distracted by components or modules that are not required or particularly useful.</li> <li><b>Usage difficulties.</b> Modern HRIS tools are often complex, multifeatured behemoths that can overwhelm many HR teams. It's important to provide appropriate training and documentation to all users before they can start using the system. This can flatten the learning curve and minimize the potential for incorrect usage.</li> <li><b>Data privacy.</b> As a repository of sensitive data, the HRIS must include controls to secure the data and protect it from leaks and breaches. The best HRIS products provide multi-layered data security through measures like role-based access controls (<a href="https://www.techtarget.com/searchsecurity/definition/role-based-access-control-RBAC">RBAC</a>), data encryption, <a href="https://www.techtarget.com/searchenterprisedesktop/definition/strong-password">strong password</a> requirements and multifactor authentication (<a href="https://www.techtarget.com/searchsecurity/definition/multifactor-authentication-MFA">MFA</a>).</li> <li><b>Regulatory compliance.</b> The HRIS must also align with regulatory requirements regarding data security and privacy. Organizations must choose HRIS software that remains compliant with regulations, even if the regulations change. Non-compliant HRIS can make the business vulnerable to costly regulatory fines and legal issues.</li> <li><b>Resistance to change. </b>Implementing an HRIS<b> </b>can meet with resistance from the HR team and also from the general employee population. To minimize resistance, decision-makers should clearly communicate the benefits of HRIS before making costly investments.</li> </ul> </section> <section class="section main-article-chapter" data-menu-title="Types of HRIS software"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Types of HRIS software</h2> <p>HRIS software is typically separated into multiple categories, such as the following:</p> <ul class="default-list"> <li><b>Comprehensive HRIS.</b> These software tools act as a centralized database for data that supports operational and tactical HR processes.</li> <li><b>Limited function. </b>These applications focus on one or two core HR processes, such as payroll, benefits management or learning management.</li> <li><b>Operational HRIS.</b> This software category will assist HR and managers with <a href="https://www.techtarget.com/searchhrsoftware/definition/talent-management-software-TM-software">talent management</a> needs, such as hiring, promotions and other personnel-related processes. Operational HRIS software focuses on making existing systems more efficient.</li> <li><b>Strategic HRIS.</b> Strategic HRIS tools aid human capital management (<a href="https://www.techtarget.com/searchhrsoftware/definition/human-capital-management-HCM">HCM</a>) processes for analysis, decision-making and goal setting.</li> <li><b>Tactical HRIS.</b> This category focuses on compliance, efficiency, recruitment, training and other internal <a href="https://www.techtarget.com/searchhrsoftware/definition/workforce-management">workforce management</a> processes.</li> </ul> <p>A variety of HRIS software is available and aimed at different sizes of organizations, ranging from <a href="https://www.techtarget.com/whatis/definition/SMB-small-and-medium-sized-business-or-small-and-midsized-business">small and medium-sized businesses</a> all the way up to large enterprises. Usually, the difference is in the range and depth of features for each process area. While most HRIS software covers a large portion of the processes described above, many systems aimed at midmarket enterprises have less depth of functionality in each feature than those aimed at large enterprises.</p> </section> <section class="section main-article-chapter" data-menu-title="Cloud-based HRIS"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Cloud-based HRIS</h2> <p>A cloud-based HRIS is delivered via the Internet and can be accessed by authorized users. These systems are designed to be intuitive and user-friendly so that both HR personnel and employees can easily access and use them.</p> <p>Some cloud HRIS systems allow system admins to customize user experiences. Such customizations may not be possible with <a href="https://www.techtarget.com/searchcloudcomputing/tip/Evaluate-on-premises-vs-cloud-computing-pros-and-cons">on-premises</a> systems. At the same time, cloud-based systems provide the same functionalities as on-prem products to streamline many core HR processes and ease employee data management. Employee self-service features are almost always included in cloud HRIS. Employees can log into the HRIS from a web browser or <a href="https://www.techtarget.com/whatis/definition/mobile-app">mobile app</a> to access their personal information, download documents and issue time-off or other requests.</p> <p>Most cloud-based HRIS are <a href="https://www.techtarget.com/searchdatacenter/definition/scalability">scalable</a>, so they can grow with an organization. With their flexible architecture, they can deal with new employees, vendors, geographies, contracts and the associated growing volumes without breaking their core functionalities. Also, they can be integrated with other HR systems to provide greater functionality for HR processes and workflows.</p> <p>Almost all cloud-native HRIS products include compliance features. These systems help to ensure that HR activities are aligned with compliance requirements and laws, including labor, immigration and employee safety laws.</p> <p>Finally, advanced cloud-based HRIS software includes <a href="https://www.techtarget.com/searchenterpriseai/definition/AI-Artificial-Intelligence">AI</a> capabilities. AI algorithms and machine learning (<a href="https://www.techtarget.com/searchenterpriseai/definition/machine-learning-ML">ML</a>) models analyze vast volumes of data and generate actionable, real-time insights that enable HR teams to upgrade their HR practices related to recruitment, talent management, learning and development, and more. Senior leaders can also use these insights to make more informed decisions to boost employee engagement and retention.</p> <p>Cloud-based HRIS products are usually provided as monthly or yearly subscriptions. The pricing is usually based on a flat-rate model or a per-employee per-month (PEPM) plan. The price will likely vary depending on factors like the number of users, features, storage, integrations and customizations. Some providers also provide on-premises and <a href="https://www.techtarget.com/searchcloudcomputing/definition/hybrid-cloud">hybrid cloud</a> options. These are usually available on-site using a <a href="https://www.techtarget.com/whatis/definition/perpetual-software-license">perpetual licensing</a> model, with additional fees incurred for the vendor to provide ongoing maintenance.</p> </section> <section class="section main-article-chapter" data-menu-title="The difference between an HRIS and an HRMS"> <h2 class="section-title"><i class="icon" data-icon="1"></i>The difference between an HRIS and an HRMS</h2> <p>Exact definitions of HRIS and human resources management system (HRMS) vary, but many experts believe that HRMSes offer greater functionality by adding talent management and HCM options to human resource information systems.</p> <p>The talent management functions often include the following:</p> <ul class="default-list"> <li>Employee onboarding processes.</li> <li>Succession planning.</li> <li>Career development planning.</li> <li>Learning management.</li> </ul> <p>The HCM functions often include:</p> <ul class="default-list"> <li>Labor tracking, typically as a system that tracks all necessary work and distributes that work to workers, often in hourly roles, such as in manufacturing plants.</li> <li>Time entry and evaluation.</li> <li>Workforce management.</li> </ul> <div class="youtube-iframe-container"> <iframe id="ytplayer-0" src="https://www.youtube.com/embed/eiLRZfcHovA?autoplay=0&modestbranding=1&rel=0&widget_referrer=null&enablejsapi=1&origin=https://www.techtarget.com" type="text/html" height="360" width="640" frameborder="0" loading="lazy"></iframe> </div> </section> <section class="section main-article-chapter" data-menu-title="Comparing HRIS vs. HRMS vs. HCM vs. HXM"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Comparing HRIS vs. HRMS vs. HCM vs. HXM</h2> <p>HRIS is commonly used with <a href="https://www.techtarget.com/searchhrsoftware/feature/HRIS-vs-HRMS-vs-HCM-Key-differences-and-similarities">similar terms such as HRMS, HCM</a> and HXM. Although they might be used interchangeably colloquially, these terms have subtle differences.</p> <ul class="default-list"> <li><b>HRMS.</b> An HRMS is a set of software applications that HR professionals use to manage HR functions. It refers to more overarching software that uses HRIS but also features more complex functionalities involved in talent management.</li> <li><b>HCM.</b> Human capital management is a comprehensive set of practices and tools used for recruiting, managing and developing employees. HCM also refers to a category of software organizations use to automate recruitment, management and workforce development. HCM software application suites enable HR teams to handle numerous HCM functions, including recruiting and performance management.</li> <li><b>HXM.</b> Human experience management (HXM) is a process that focuses on collecting and analyzing data related to the employee experience. The goal of HXM is to improve the overall employee experience. HXM software focuses on linking core HR, payroll, talent management and people analytics processes.</li> </ul> <p>In general, HRIS refers to technology that stores employee data and automates core HR functions. It thus acts as a centralized database for employee information. HCM software includes features to streamline employee-centric processes, such as talent management, time tracking, and labor management. HRMS products include HRIS functions and HCM features to streamline payroll, talent management, analytics and more. HXM refers explicitly to software used to manage employee experience.</p> <p>HCM is both a set of HR processes and the name of a software category. HRMS, in contrast, is a set of integrated software applications and other technologies used to manage HR processes. HRMS is nearly synonymous with the less commonly used HRIS. HRIS, however, can mean just the core administrative system.</p> <p>Core HR technology systems have long been marketed under HRIS and HRMS labels, but HCM has recently begun to displace both terms.</p> <div class="youtube-iframe-container"> <iframe id="ytplayer-1" src="https://www.youtube.com/embed/jW_5GGj0zUM?autoplay=0&modestbranding=1&rel=0&widget_referrer=null&enablejsapi=1&origin=https://www.techtarget.com" type="text/html" height="360" width="640" frameborder="0" loading="lazy"></iframe> </div> </section> <section class="section main-article-chapter" data-menu-title="Key considerations when choosing an HRIS"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Key considerations when choosing an HRIS</h2> <p>Investing in an HRIS is a massive undertaking for any organization. Before selecting software, CHROs should ensure the other appropriate <a href="https://www.techtarget.com/searchcio/definition/stakeholder">stakeholders</a> are involved and that all the stakeholders thoroughly assess current and future needs. While HRIS selection isn't a linear process, the following are some general steps to consider before adopting an HRIS:</p> <ol class="default-list"> <li><b>Initial assessment.</b> This step identifies an organization's biggest pain points and challenges with current HR processes. This step includes determining who will participate in the HRIS selection process and whether it will be conducted internally. Smaller businesses with limited staff and resources might consider hiring consultants.</li> <li><b>Collect internal data. </b>Conduct an internal audit of the features and functionalities necessary for the company's HRIS software. This can be accomplished by interviewing employees, managers and stakeholders, and observing day-to-day operations. Employee input is essential, as it helps make adopting the new HRIS easier. For example, a company with a large group of <a href="https://www.techtarget.com/searchmobilecomputing/definition/telecommuting">telecommuters</a> or employees who travel regularly might give feedback to replace the time-clock-based system with an online timekeeping system. A time clock-based system makes more sense in a manufacturing environment, as employees perform all work on-site.</li> <li><b>Create a checklist. </b>After the internal evaluation, a checklist should be developed, noting all the determined requirements. This checklist should be updated regularly as the company goes through various research phases.</li> <li><b>Assess the budgetary limitations. </b>The project's budget can be determined once the list of requirements has been finalized. This can be achieved by performing a <a href="https://www.techtarget.com/searcherp/definition/budgeting-planning-and-forecasting-BPF">budgeting</a> exercise, which investigates budgeting and technological and time constraints that the company might potentially face. HRIS vendors can also assist in narrowing down company costs and budgets. Cost assessments can be broken down into software, hardware, implementation and support. For example, hardware costs aren't a factor if the company goes with a cloud-based HRIS, whereas the software will typically be priced as a monthly subscription.</li> <li><b>Select a vendor.</b> Create a vendor checklist and <a href="https://www.techtarget.com/searchhrsoftware/feature/HR-software-selection-How-to-ask-the-right-questions">evaluate HRIS vendors</a> against the organization's needs and requirements to create a shortlist of potential vendors. After all the insights from the initial and internal assessments are gathered, companies can prepare a <a href="https://www.techtarget.com/searchitchannel/definition/request-for-proposal">request for proposal</a>. Once a vendor is selected, the company can decide whether to go with a basic package and add more modules and functionalities as the business scales or start with a comprehensive package.</li> </ol> </section> <section class="section main-article-chapter" data-menu-title="HRIS vendors"> <h2 class="section-title"><i class="icon" data-icon="1"></i>HRIS vendors</h2> <p>Numerous companies provide feature-rich HRIS software. Below is an unranked sample list of HRIS providers:</p> <ul class="default-list"> <li>SAP SuccessFactors.</li> <li>Gusto.</li> <li>Rippling.</li> <li>BambooHR.</li> <li>FactoHR.</li> <li>Workday.</li> <li>Namely.</li> <li>Optimum.</li> <li>TriNet HR Plus.</li> </ul> <p>Some HRIS platforms are well-suited for mid-size companies, including products from the following:</p> <ul class="default-list"> <li>BambooHR.</li> <li>Rippling.</li> <li>Gusto.</li> <li>Paycor.</li> <li>ADP.</li> </ul> <p>Some of the mentioned below can also support the HRIS needs of smaller firms:</p> <ul class="default-list"> <li>SAP SuccessFactors.</li> <li>BambooHR.</li> <li>UKG Pro.</li> <li>TriNet HR Plus.</li> </ul> </section> <section class="section main-article-chapter" data-menu-title="Future of HRIS technology"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Future of HRIS technology</h2> <p>HRIS technology is constantly evolving. While automated HRIS isn't new, the features and functionalities of the systems are expected to become more efficient and useful to cater to the growing trend of hybrid work and <a href="https://www.techtarget.com/searchcio/definition/globalization">globalization</a>. When employees work in different locations, departments and specializations, having an HRIS in place is essential.</p> <p>Evolving trends with HRIS technology include:</p> <ul class="default-list"> <li><b>Artificial intelligence and machine learning. </b>As automated technologies advance, the future of HRIS will likely feature the integration of AI and ML to help users make intuitive decisions. These intelligent systems will be able to detect what employees want to accomplish, such as changing benefits selection or requesting time off. This will also enable AI- and ML-based HRIS products to offer proactive solutions, such as using AI-powered cloud technologies for pay calculation and time tracking. AI-based <a href="https://www.techtarget.com/searchenterpriseai/definition/facial-recognition">facial recognition</a> could eliminate the need for passwords, ID badges or waiting in line to sign in to work.</li> <li><b>Performance management.</b> HRIS products are introducing comprehensive performance management features that can completely change how employee performance is tracked, rated and communicated. Many organizations have been slow to adapt to the changing HR trends. However, as HRIS technology becomes more advanced, these organizations will be able to adopt new performance management programs to give them more options for performance reviews.</li> <li><b>Compliance and regulations.</b> Companies can avoid compliance violations and penalties by moving away from complicated payroll and seeking access to <a href="https://www.techtarget.com/searchitoperations/definition/compliance-automation">automated compliance</a>. Future HRIS platforms will provide automated compliance to enable companies to keep up with complex and evolving compliance laws.</li> <li><b>Software as a service.</b> On-premises HR systems or <a href="https://www.techtarget.com/searchcloudcomputing/definition/Software-as-a-Service">SaaS</a> options are being widely adopted, making it easier for organizations to access HR information from anywhere. This trend will likely expand in the next few years and play an important role in how workplaces and employees function collectively.</li> <li><b>Advanced integrations of HR systems.</b> Payroll and HRMS both play important but separate roles. For most organizations, payroll typically maintains corresponding pay and time data, whereas HRMS stores all employee data. Modern HRIS programs provide advanced integrations, which prevent the disruption of a business's current ecosystems by integrating these complementary systems into one platform. This way, businesses can connect pay and time with employee data and use these factors to manage performance, engagement and productivity. Cloud-based HRIS tools also play an important role in sending data to both local and global systems within payroll and HR.</li> <li><b>Predictive analytics for workforce planning.</b> The predictive analytics provided by some HRIS tools let HR professionals make more data-driven decisions. For example, an HRIS can predict attrition rates by <a href="https://www.techtarget.com/searchcustomerexperience/definition/real-time-analytics">analyzing real-time data</a> and historical data.</li> <li><b>Employee self-service.</b> Current HRIS tools provide employees with self-service portals, letting employees access their personal information or perform tasks such as managing benefits or requesting vacation time.</li> </ul> <div class="youtube-iframe-container"> <iframe id="ytplayer-2" src="https://www.youtube.com/embed/uzL1ZqzlWcw?autoplay=0&modestbranding=1&rel=0&widget_referrer=null&enablejsapi=1&origin=https://www.techtarget.com" type="text/html" height="360" width="640" frameborder="0" loading="lazy"></iframe> </div> </section> <section class="section main-article-chapter" data-menu-title="What do HRIS analysts do?"> <h2 class="section-title"><i class="icon" data-icon="1"></i>What do HRIS analysts do?</h2> <p>In general, HRIS analysts ensure efficient organization and presentation of information concerning all features of HR functions within a company. HRIS analysts are highly trained HR professionals with skills in both IT and HR, who are responsible for managing and <a href="https://www.techtarget.com/searchhrsoftware/answer/Why-is-HRIS-maintenance-so-important">maintaining the HRIS</a> and presenting relevant and beneficial data on employee productivity, attendance, training and pay.</p> <p>HRIS analysts also ensure that IT departments adhere to HR regulations, provide necessary resources to employees and arrange for appropriate system updates and upgrades.</p> <p>Some of the other responsibilities of HRIS analysts might include the following:</p> <ul class="default-list"> <li>Translate business requirements and user needs into clear technical requirements.</li> <li>Design, implement and maintain the HRIS.</li> <li>Troubleshoot HRIS issues.</li> <li>Offer technical support to HR users and other employees.</li> <li>Evaluate the HRIS to identify areas of improvement and make recommendations.</li> <li>Implement or add measures to strengthen data quality, security and privacy.</li> <li>Provide reports and insights to senior leaders to assist with decision-making.</li> </ul> <p>Large organizations might employ several HRIS analysts to focus on specific HR tasks, such as employee benefits, compensation or training.</p> <p>HRIS analysts can be valuable additions to an organization's HR department, so CHROs should consider hiring one or more if their company does not currently employ any HRIS analysts. HRIS analysts can provide these specific benefits:</p> <ul class="default-list"> <li>Customer service for both the employee and management users of the HRIS.</li> <li>Advice based on analysis of HRIS processes and outcomes.</li> <li>Data entry for the large amounts of employee information.</li> <li>Assurance that employee information and data are kept confidential and secure.</li> <li>Increased accuracy due to the analyst's editing and confirming of data before it's reported.</li> </ul> <p>Most companies hire HRIS analysts who have at least a bachelor's degree in <a href="https://www.techtarget.com/searchdatacenter/definition/IT">information technology</a>, human resources or business administration. Familiarity with major HRIS software is almost always mandatory, while experience with IT project management, data analytics and <a href="https://www.techtarget.com/searchsoftwarequality/definition/systems-development-life-cycle">system development lifecycle</a> is considered a plus. Additionally, HRIS analysts with strong communication and problem-solving skills, critical thinking skills and attention to detail are more likely to be considered for hiring.</p> <p>Many companies don't require their HRIS analysts to be certified by a recognized institution. However, HRIS analysts may provide proof of their excellence in the field and commitment to HR by obtaining certifications from accredited and globally-recognized entities, such as the International Association for Human Resource Information Management (<a target="_blank" href="https://www.ihrim.org/" rel="noopener">IHRIM</a>).</p> <p>In 2025, the average base salary for an HRIS analyst in the U.S. is $83,101, according to Glassdoor. Experienced HRIS analysts can earn as much as $119,810 per year. Salaries tend to be higher in large cities like New York, Los Angeles, Denver and Seattle. Actual salaries for HRIS analysts depend on many factors, including the number of years of experience, location and education level.</p> <p><i>To help you whittle down your HR software shortlist, learn the </i><a href="https://www.techtarget.com/searchhrsoftware/tip/The-7-best-HR-software-and-tool-options-to-consider"><i>pros and cons of some top HR software vendors and tools</i></a><i>, and get buying tips to ensure your purchase is a success.</i></p> </section> A human resources information system (HRIS) is software that aids organizations in maintaining detailed employee information and managing and automating core human resources (core HR) processes. https://cdn.ttgtmedia.com/visuals/digdeeper/5.jpg https://www.techtarget.com/searchhrsoftware/definition/HRIS Tue, 24 Mar 2026 13:30:00 GMT What is HRIS (human resources information system)? <p>Material requirements planning (MRP) is a system for calculating the materials and components needed to manufacture a product. It consists of three primary steps: taking inventory of the materials and components on hand, identifying which additional ones are needed and then scheduling their production or purchase.</p> <p>Chief operating officers (COOs), chief supply chain officers (CSCOs) and any other C-suite members who work on the supply chain must ensure their companies are carrying out MRP in the proper way and should consider whether the technology they are using to carry out MRP is meeting their organization’s needs.</p> <section class="section main-article-chapter" data-menu-title="Why is MRP important?"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Why is MRP important?</h2> <p>MRP, which is done primarily <a href="https://www.techtarget.com/searcherp/tip/Top-MRP-software-for-you-to-try">through specialized software</a>, helps ensure that the right inventory is available for the production process exactly when it is needed and at the lowest possible cost. As such, MRP improves the efficiency, flexibility and profitability of manufacturing operations. It can make factory workers more productive, improve product quality and minimize material and labor costs. MRP also helps manufacturers respond more quickly to increased demand for their products and avoid production delays and inventory stockouts that can result in lost customers, which in turn contributes to revenue growth and stability.</p> <p>MRP is widely used by manufacturers and has undeniably been one of the key enablers in the growth and wide availability of affordable consumer goods and, consequently, has raised the standard of living in most countries. Without a way to automate the complex calculations and <a href="https://www.techtarget.com/searchdatamanagement/definition/data-management">data management</a> of MRP processes, it is unlikely that individual manufacturers could have scaled up operations as rapidly as they have in the half century since MRP software arrived.</p> <div class="youtube-iframe-container"> <iframe id="ytplayer-0" src="https://www.youtube.com/embed/Dis3UYcEXVw?autoplay=0&modestbranding=1&rel=0&widget_referrer=null&enablejsapi=1&origin=https://www.techtarget.com" type="text/html" height="360" width="640" frameborder="0" loading="lazy"></iframe> </div> </section> <section class="section main-article-chapter" data-menu-title="How does MRP work?"> <h2 class="section-title"><i class="icon" data-icon="1"></i>How does MRP work?</h2> <p>MRP uses information from the bill of materials (<a href="https://www.techtarget.com/searcherp/definition/bill-of-materials-BoM">BOM</a>), inventory data and the <a href="https://www.techtarget.com/searcherp/tip/MRP-vs-MPS-What-are-the-differences">master production schedule</a> to calculate the required materials and when they will be needed in the manufacturing process.</p> <p>The BOM is a hierarchical list of all the materials, subassemblies and other components needed to make a product, along with their quantities, each usually shown in a parent-child relationship. The finished good is the parent at the top of the hierarchy.</p> <p>The inventory items in the BOM are classified as either <em>independent demand</em> or <em>dependent demand</em>. An independent demand item is the finished good at the top of the hierarchy. Manufacturers determine its amount by considering confirmed orders and examining market conditions, past sales and other indicators to create a forecast, then decide how many to make to meet the expected demand.</p> <p>Dependent demand items, in contrast, are the raw materials and components needed to make the finished product. For each of these items, demand depends on how many are needed to make the next-highest component in the BOM hierarchy.</p> <p>MRP is the system most companies use to track and manage all of these dependencies and to calculate the number of items needed by the dates specified in the master production schedule. To put it another way, MRP is an inventory management and control system for ordering and tracking the items needed to make a product.</p> <p>Lead time -- the period from when an order is placed and the item delivered -- is another key concept in MRP. There are many types of lead times. Two of the most common are material lead time (the time it takes to order materials and receive them) and factory or production lead time (how long it takes to make and ship the product after all materials are in). Customer lead time denotes the time between the customer order and final delivery. The MRP system calculates many of these lead times, but some are chosen by the operations managers and entered manually.</p> <figure class="main-article-image full-col" data-img-fullsize="https://www.techtarget.com/rms/onlineimages/erp-bill_of_materials_2.png"> <img data-src="https://www.techtarget.com/rms/onlineimages/erp-bill_of_materials_2_mobile.png" class="lazy" data-srcset="https://www.techtarget.com/rms/onlineimages/erp-bill_of_materials_2_mobile.png 960w,https://www.techtarget.com/rms/onlineimages/erp-bill_of_materials_2.png 1280w" alt="Diagram of a multilevel bill of materials (BOM)" height="465" width="560"> <figcaption> <i class="icon pictures" data-icon="z"></i>The bill of materials specifies the items needed to make a product and is a key data source in MRP. </figcaption> <div class="main-article-image-enlarge"> <i class="icon" data-icon="w"></i> </div> </figure> </section> <section class="section main-article-chapter" data-menu-title="MRP in manufacturing"> <h2 class="section-title"><i class="icon" data-icon="1"></i>MRP in manufacturing</h2> <p>MRP is essential to the efficiency, effectiveness and ultimately the profitability of a manufacturing operation. Without the right raw materials and components on hand, manufacturers can't hope to keep up with the demand for products at the optimal cost and quality. They will also be less able to respond to fluctuations in demand by adjusting production.</p> <p>MRP can also make the later stages of production, such as assembly and packaging, proceed more smoothly and predictably by removing most of the uncertainty over inventory and minimizing the time needed to manage it.</p> <p>MRP is useful in both <a href="https://www.techtarget.com/searcherp/definition/discrete-manufacturing">discrete manufacturing</a>, in which the final products are distinct items that can be counted -- such as bolts, subassemblies or automobiles -- and <a href="https://www.techtarget.com/searcherp/definition/process-manufacturing">process manufacturing</a>, which results in bulk products, including chemicals, soft drinks and detergent, that can't be separately counted or easily broken down into their constituent parts.</p> </section> <section class="section main-article-chapter" data-menu-title="Benefits of MRP"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Benefits of MRP</h2> <p>The primary objective of MRP is to make sure that materials and components are available when needed in the production process and that manufacturing takes place on schedule. <a href="https://www.techtarget.com/searcherp/tip/Benefits-of-MRP-software">Additional benefits of MRP</a> are as follows:</p> <ul class="default-list"> <li>Reduced customer lead times to improve customer satisfaction.</li> <li>Reduced inventory costs.</li> <li>Effective <a href="https://www.techtarget.com/searcherp/definition/inventory-management">inventory management</a> and optimization -- by acquiring or manufacturing the optimal amount and type of inventory, companies can minimize the risk of stock-outs, and their negative impact on customer satisfaction, sales and revenue, without spending more than necessary on inventory.</li> <li>Improved manufacturing efficiency by using accurate production planning and scheduling to optimize the use of labor and equipment.</li> <li>Improved labor productivity.</li> <li>More competitive product pricing.</li> </ul> </section> <section class="section main-article-chapter" data-menu-title="Disadvantages of MRP"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Disadvantages of MRP</h2> <p>MRP has drawbacks, including the following:</p> <ul class="default-list"> <li>Oversupply of inventory. While MRP is designed to ensure adequate inventory levels at the required times, companies can be tempted to hold more inventory than is necessary, which COOs and CSCOs may find drives up inventory costs. An MRP system anticipates shortages sooner, which can lead to overestimating inventory lot sizes and lead times, especially in the early days of deployment before users gain the experience to know the actual amounts needed.</li> <li>Lack of flexibility. MRP is also somewhat rigid and simplistic in how it accounts for lead times or details that affect the master production schedule, such as the efficiency of factory workers or issues that can delay delivery of materials.</li> <li>Data integrity requirements. MRP is highly dependent on having accurate information about key inputs, especially demand, inventory and production. If one or two inputs are inaccurate, errors can be magnified at later stages. Data integrity and data management are thus essential to effective use of MRP systems.</li> </ul> <p>To address these shortcomings of MRP, many manufacturers use advanced planning and scheduling (APS) software, which uses sophisticated math and logic to provide more accurate and realistic estimates of lead times. Unlike most MRP systems, APS software accounts for production capacity, which can have a significant impact on availability of materials.</p> </section> <section class="section main-article-chapter" data-menu-title="History of MRP"> <h2 class="section-title"><i class="icon" data-icon="1"></i>History of MRP</h2> <p>The seeds of MRP were planted early in the 20th century with the development of new models for optimizing manufacturing. In 1913, American production engineer Ford Whitman Harris developed the calculation known as economic order quantity, the amount that minimizes the cost of ordering and storing a good. Concurrently, the mass-production system invented by Henry Ford showed the value of having strict controls over the flow of materials through an assembly line. Another key driver of industrial efficiency came from the scientific management theories of Frederick Taylor, which included techniques for production planning and control and for improving the efficiency of material handling.</p> <p>With the advent of computers, systems for optimizing the manufacturing process entered a new era. When mainframe computers became commercially available in the 1950s, programmers at manufacturing companies began developing custom software to manage BOMs, inventory, production and scheduling.</p> <p>It wasn't until the 1960s, however, that the field got its modern name. That's when a small group of influential engineers championed an integrated system of computerized planning they dubbed material requirements planning. In 1964, IBM engineer Joseph Orlicky developed and formalized MRP after he studied the Toyota Production System, which was the model for the <a href="https://www.techtarget.com/searcherp/definition/lean-production">lean production</a> methodology. Then, in 1967, Orlicky's IBM colleague, Oliver Wight, co-wrote a book on production and inventory control with George Plossl, a mechanical engineer and management consultant. The three continued to collaborate and today are usually cited as the pioneers of MRP.</p> <p>It's important to note that MRP and lean production are not the same, despite their connection in Orlicky's pioneering work. In fact, they are considered by many practitioners to be antithetical, though some say MRP can help with lean production. MRP is considered a "push" production planning system -- inventory needs are determined in advance, and goods produced to meet the forecasted need -- while lean is a "pull" system in which nothing is made or purchased without evidence of actual -- not forecasted -- demand.</p> <p>Orlicky's ideas spread rapidly throughout the manufacturing sector after the 1975 publication of his book, <em>Material Requirements Planning: The New Way of Life in Production and Inventory Management. </em>By the early 1980s, there were hundreds of commercial and homegrown MRP software programs.</p> <p>MRP also received a major boost in the 1970s from the educational efforts of the American Production and Inventory Control Society (APICS), after Orlicky, Plossl and Wight pushed the association to evangelize for MRP. APICS became the main source of MRP education and certification and continues in that role today, having expanded over the decades into operations management and <a href="https://www.techtarget.com/searcherp/Guide-to-supply-chain-management">supply chain management</a>.</p> <p>Orlicky died in 1986. A second edition of his book, updated by Plossl, was released in 1994. The current version, <em>Orlicky's Material Requirements Planning, Third Edition</em> is a 2011 update by consultants Carol Ptak and Chad Smith. It adds advice on how to use MRP to run a "demand-driven" planning process that uses actual sales orders, rather than the typical MRP method of a sales forecast, to calculate material requirements. Called demand-driven material requirements planning (DDMRP), this newer "pull" approach is controversial and viewed by some as a violation of important principles established by Orlicky.</p> </section> <section class="section main-article-chapter" data-menu-title="MRP vs. ERP"> <h2 class="section-title"><i class="icon" data-icon="1"></i>MRP vs. ERP</h2> <p>An extension of MRP, developed by Wight in 1983 and called manufacturing resource planning (MRP II), broadened the planning process to include other resources in the company, such as financials, and added processes for product design, capacity planning, <a href="https://www.techtarget.com/whatis/definition/cost-management">cost management</a>, shop floor control and <a href="https://www.techtarget.com/searcherp/definition/sales-and-operations-planning-SOP">sales and operations planning</a>, among many others.</p> <figure class="main-article-image full-col" data-img-fullsize="https://www.techtarget.com/rms/onlineImages/erp-mrp_vs_mrpii_vs_erp-f.png"> <img data-src="https://www.techtarget.com/rms/onlineImages/erp-mrp_vs_mrpii_vs_erp-f_mobile.png" class="lazy" data-srcset="https://www.techtarget.com/rms/onlineImages/erp-mrp_vs_mrpii_vs_erp-f_mobile.png 960w,https://www.techtarget.com/rms/onlineImages/erp-mrp_vs_mrpii_vs_erp-f.png 1280w" alt="How MRP differs from MRP II and ERP" height="541" width="560"> <figcaption> <i class="icon pictures" data-icon="z"></i>MRP II expanded MRP to other business functions and was renamed ERP. </figcaption> <div class="main-article-image-enlarge"> <i class="icon" data-icon="w"></i> </div> </figure> <p>In 1990, the analyst firm Gartner coined the term enterprise resource planning (<a href="https://www.techtarget.com/searcherp/definition/ERP-enterprise-resource-planning">ERP</a>) to denote a still more expanded and generalized type of MRP II that took into account other major functions of a business, such as accounting, human resources and <a href="https://www.techtarget.com/searcherp/definition/supply-chain-management-SCM">supply chain management</a>, all of it managed in a centralized database. Both MRP and MRP II are considered direct predecessors of ERP.</p> <p>ERP quickly expanded to other industries, including services, banking and retail, that did not need an MRP component. However, MRP is still an important part of the ERP software used by manufacturers.</p> </section> Material requirements planning (MRP) is a system for calculating the materials and components needed to manufacture a product. https://cdn.ttgtmedia.com/visuals/digdeeper/4.jpg https://www.techtarget.com/searcherp/definition/material-requirements-planning-MRP Tue, 10 Mar 2026 11:00:00 GMT material requirements planning (MRP) <p>Performance management software is a tool that enables human resources (HR) teams to measure and track the performance of employees and to implement appropriate programs or strategies to ensure that employee performance is aligned with the organization's business objectives and goals. It helps HR personnel and line managers evaluate how team members are performing and whether they are on track toward achieving specific performance and productivity goals.</p> <p>CHROs must ensure their company’s performance management software is right for their organization and is helping the HR department and other employees achieve performance management goals rather than hindering the process. Performance management software can help improve employee performance and employee engagement, which can improve the company’s overall performance at other goals.</p> <p>Additionally, by using data, performance management software helps managers identify performance gaps in individual employees. Managers can then address the gaps by working with the employee and providing support, mentoring or additional job training.</p> <p>Performance management software systems are overseen by the HR department. They fit under the umbrella of <a href="https://www.techtarget.com/searchhrsoftware/definition/talent-management-software-TM-software">talent management systems</a>. HR trains managers and employees in the software's use to get the most out of its features for performance measurement, management and improvement.</p> <section class="section main-article-chapter" data-menu-title="What does performance management software do?"> <h2 class="section-title"><i class="icon" data-icon="1"></i>What does performance management software do?</h2> <p>Performance management software is designed to improve business performance by spurring employee productivity. It works to ensure individual employees and teams are engaged and in alignment with <a href="https://www.techtarget.com/searchcio/definition/organizational-goals">organizational goals</a>.</p> <p>These systems enable businesses to adjust individual employee goals and expectations as conditions change. Performance management tools provide real-time data that facilitates real-time performance tracking, goal setting and continuous feedback -- something that annual reviews can't do. Annual reviews, according to critics, are too focused on the past and not on forward-looking needs.</p> </section> <section class="section main-article-chapter" data-menu-title="Goals of performance management software"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Goals of performance management software</h2> <p>Performance management systems are widely considered next-generation workforce management software. These systems help companies to continually monitor employee performance, while giving employees continuous feedback and tailored support.</p> <p>Performance management software can track individual contributions to a team, as well as that team's ability to meet business objectives. This helps to tie employees' performance to the company's bottom line and identify where there are mismatches that need to be addressed.</p> <p>Improving <a href="https://www.techtarget.com/searchhrsoftware/definition/employee-engagement">employee engagement</a> is another goal of performance management software. An employee can log in to a dashboard to see their individual performance goals and their progress toward meeting them. They can also track their efforts on specific projects, assess their progress and if they need managerial or <a href="https://www.cfo.com/spons/the-cfos-dilemma-building-a-scalable-talent-strategy-with-an-overloaded-h/748047/" target="_blank" rel="noopener">HR support</a>. Managers set employee goals and can use the tool to measure individual performance against both individual and project goals.</p> <p>Performance management software ends the tedious -- and often ineffective -- end-of-year annual review process for managers. Instead, it can measure, assess and evaluate employee performance throughout the year. It can also identify problems early and address them before they grow into bigger issues that negatively affect the organization.</p> <p>Managers and HR teams can use performance management software for the following:</p> <ul class="default-list"> <li>Set clear goals and objectives for employees.</li> <li>Perform frequent check-ins with employees to assess their progress.</li> <li>Provide regular and real-time feedback to employees to collectively address problems that are a priority.</li> <li>Provide necessary support to improve employee engagement, <a href="https://www.techtarget.com/searchhrsoftware/definition/employee-retention">retention</a> and profitability.</li> <li>Increase transparency in the performance review process through regular communication with employees.</li> </ul> </section> <section class="section main-article-chapter" data-menu-title="Benefits of performance management software"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Benefits of performance management software</h2> <p>Performance management software enables managers, <a href="https://aibusiness.com/verticals/when-ai-meets-hr-here-s-what-happens#close-modal" target="_blank" rel="noopener">HR staff</a>, CHROs and other stakeholders to measure employee performance in a consistent and tangible manner and can assess how employee performance is impacting the organization's performance. Such assessments are important to determine if employees are performing at the levels expected of them and whether their work is contributing to the company's overall performance and growth.</p> <p>A data-driven performance management system shows how employees are behaving at work, their strengths and weaknesses, and whether they need additional support to improve their performance. Leaders, including CHROs, can use the insights from the system to institute the required improvements, which can then enhance the performance and productivity of the entire workforce. Additionally, the support provided by the organization can increase employee motivation, improve retention, reduce turnover, and maximize revenue per employee and overall profitability.</p> </section> <section class="section main-article-chapter" data-menu-title="Key features of performance management software"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Key features of performance management software</h2> <p>At the least, performance management software enables management and employees to set specific, measurable, achievable, relevant and time-bound goals, or <a href="https://www.techtarget.com/whatis/definition/SMART-SMART-goals">SMART goals</a>. These goals provide a tangible and measurable way to set objectives and assess employee performance against those objectives.</p> <figure class="main-article-image full-col" data-img-fullsize="https://www.techtarget.com/rms/onlineImages/fin_apps-continuous_performance_management.jpg"> <img data-src="https://www.techtarget.com/rms/onlineImages/fin_apps-continuous_performance_management_mobile.jpg" class="lazy" data-srcset="https://www.techtarget.com/rms/onlineImages/fin_apps-continuous_performance_management_mobile.jpg 960w,https://www.techtarget.com/rms/onlineImages/fin_apps-continuous_performance_management.jpg 1280w" alt="Diagram of continuous performance management process." height="448" width="560"> <figcaption> <i class="icon pictures" data-icon="z"></i>Five steps of performance management </figcaption> <div class="main-article-image-enlarge"> <i class="icon" data-icon="w"></i> </div> </figure> <p>Most performance management software incorporates a continuous feedback mechanism for regular and open communication between employees and managers. Managers can assess employee performance, regularly communicate their expectations and set up performance improvement plans. All this can help employees to address gaps immediately instead of having to wait for the end of year review -- by which time, it may be too late to implement the feedback.</p> <p>Many systems also enable 360-degree feedback, which includes not only input from an employee's supervisor, but also from peers and subordinates. Such a multirater mechanism provides deeper insights into a person's <a href="https://www.techtarget.com/whatis/feature/Signs-of-toxic-workplace-culture">work behaviors</a> and relationships, enabling managers to better evaluate their performance and make better decisions regarding matters like performance improvement, training and promotions.</p> <p>Performance management systems use dashboards for quick and collaborative reviews, while downloadable reports provide information about individual, project and team performance. Some systems may also include features like review templates, automated reminders and employee ranking.</p> <div class="youtube-iframe-container"> <iframe id="ytplayer-0" src="https://www.youtube.com/embed/uzL1ZqzlWcw?autoplay=0&modestbranding=1&rel=0&widget_referrer=null&enablejsapi=1&origin=https://www.techtarget.com" type="text/html" height="360" width="640" frameborder="0" loading="lazy"></iframe> </div> <p>Effective performance management programs seamlessly interact with other tools, such as workforce analytics. Data can be analyzed, for instance, against reporting from financial management systems and sales performance management systems. Analysis of employee data can be used to make decisions related to hiring, training and development, goal setting and promotions.</p> <p>Some performance management tools also include features like the following:</p> <ul class="default-list"> <li><b>Employee reward and recognition.</b> Managers can analyze and compare employees' performance to determine who should be rewarded and in what way.</li> <li><a href="https://www.techtarget.com/searchcio/definition/learning-management-system"><b>Learning management system</b></a><b>.</b> Supervisors and HR personnel can assess employees' current skills and nominate them for skill development and career progression training programs.</li> <li><b>Customizable surveys. </b>Decision-makers can send out surveys to measure employee engagement and gather employee feedback on various aspects related to the company.</li> <li><b>Security features.</b> Reliable performance management tools include security features to safeguard employee data from breaches, such as <a href="https://www.techtarget.com/searchsecurity/definition/encryption">encryption</a> and <a href="https://www.techtarget.com/searchsecurity/definition/access-control">access controls</a>. Some tools also back up all data at regular intervals to the cloud to enable fast recovery from data loss incidents.</li> </ul> </section> <section class="section main-article-chapter" data-menu-title="Future effects of performance management software"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Future effects of performance management software</h2> <p><a href="https://www.techtarget.com/searchenterpriseai/definition/AI-Artificial-Intelligence">AI</a> is expected to have a positive effect on performance management systems. For example, gender or ethnic bias in performance reviews has been identified in multiple studies as a problem for some groups of workers in the workplace. AI-enabled tools could help to remove such biases. Training such tools with diverse data sets that include a wide range of demographic characteristics, including genders and ethnicities, could help to improve the performance of the underlying <a href="https://www.techtarget.com/whatis/definition/algorithm">algorithm</a>, which, in turn, could result in fairer, less biased output.</p> <p>AI-enabled tools can also be used to detect language patterns that may signal bias. These patterns can help recruiters to make better recruitment decisions. For this reason, such tools are already being used for <a href="https://www.techtarget.com/searchhrsoftware/definition/recruitment-management-system">recruitment management</a>.</p> <p>However, performance management systems include a high volume of private data, and AI being able to access that data could lead to issues. CHROs should make sure they are aware of this and other potential problems associated with using AI for performance management before adding the technology as part of the performance review process.</p> <p><em>Inefficiencies in the performance management process can result in serious consequences, including discrimination or retaliation claims against a company. It is essential for HR personnel to be well versed in these critical issues. Explore <a href="https://www.techtarget.com/searchhrsoftware/tip/5-performance-management-challenges-and-how-to-fix-them">key issues in performance management</a>.</em></p> </section> Performance management software is a tool that enables human resources (HR) teams to measure and track the performance of employees and to implement appropriate programs or strategies to ensure that employee performance is aligned with the organization's business objectives and goals. https://cdn.ttgtmedia.com/visuals/digdeeper/5.jpg https://www.techtarget.com/searchhrsoftware/definition/performance-management-software Tue, 24 Feb 2026 14:30:00 GMT What is performance management software? <p>Data visualization translates information into charts, maps or other graphics to show patterns, trends and outliers in a way that can be grasped quickly. The goal is to make complex data easier to understand and act on.</p> <p>Data visualization is a core component of both business intelligence (<a href="https://www.techtarget.com/searchbusinessanalytics/definition/business-intelligence-BI">BI</a>) and <a href="https://www.techtarget.com/searchenterpriseai/definition/data-science">data science</a> applications. It spans the data analytics process, from initial data exploration to communicating the final results. Visualizing data helps analysts find relationships in data sets, validate analytics models, track key performance indicators (<a href="https://www.techtarget.com/searchbusinessanalytics/definition/key-performance-indicators-KPIs">KPIs</a>), then explain findings to business executives and other end users.</p> <p>BI and data science teams commonly embed data visualizations in interactive <a href="https://www.techtarget.com/searchbusinessanalytics/definition/business-intelligence-dashboard">business intelligence dashboards</a> and static reports. Visualization also supports more elaborate <a href="https://www.techtarget.com/searchcio/definition/data-storytelling">data storytelling</a>, which combines data, narrative and visuals to offer insights and inform decisions. In addition, business users often create visualizations themselves in <a href="https://www.techtarget.com/searchbusinessanalytics/definition/self-service-business-intelligence-BI">self-service BI</a> environments.</p> <p>Virtually every professional discipline relies on data visualization. Corporate executives monitor performance and inform stakeholders. Marketers optimize campaigns. Supply chain managers track shipments and manage inventory. Computer scientists explore advancements in artificial intelligence (<a href="https://www.techtarget.com/searchenterpriseai/definition/AI-Artificial-Intelligence">AI</a>).</p> <p>Without data visualization, the meaning of BI data would be less obvious to business users. It's central to <a href="https://www.techtarget.com/searchbusinessanalytics/definition/advanced-analytics">advanced analytics</a> for similar reasons. When data scientists build predictive analytics or <a href="https://www.techtarget.com/searchenterpriseai/definition/machine-learning-ML">machine learning</a> models, visualizing the outputs helps them monitor results and confirm that the models perform as intended more easily than interpreting raw numerical data. Visualization also plays a key role in <a href="https://www.techtarget.com/searchdatamanagement/definition/big-data">big data</a> projects, where businesses need to understand large volumes of data.</p> <section class="section main-article-chapter" data-menu-title="Why is data visualization important?"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Why is data visualization important?</h2> <p>Data visualization provides a quick and effective way to communicate information that's critical to decision-making in organizations.</p> <p>While business professionals have different areas and levels of expertise, well-designed visualizations make data analysis easier to understand, showing at a glance what is happening or has changed in a particular area. Executives, business managers and operational employees can act faster based on this visual evidence.</p> <p>Among other things, visualizations help businesses to:</p> <ul class="default-list"> <li>Identify factors that influence customer behavior.</li> <li>Find products or services that need to be improved.</li> <li>Make information more memorable for stakeholders.</li> <li>Decide when and where to deploy specific products.</li> <li>Predict product demand, sales or revenue.</li> </ul> <figure class="main-article-image full-col" data-img-fullsize="https://www.techtarget.com/rms/onlineImages/ba-data_visualization_timeline-f.png"> <img data-src="https://www.techtarget.com/rms/onlineImages/ba-data_visualization_timeline-f_mobile.png" class="lazy" data-srcset="https://www.techtarget.com/rms/onlineImages/ba-data_visualization_timeline-f_mobile.png 960w,https://www.techtarget.com/rms/onlineImages/ba-data_visualization_timeline-f.png 1280w" alt="Timeline of data visualization's progress throughout centuries" height="594" width="560"> <figcaption> <i class="icon pictures" data-icon="z"></i>The timeline depicting the history of data visualization starts hundreds of years before the introduction of modern technology. </figcaption> <div class="main-article-image-enlarge"> <i class="icon" data-icon="w"></i> </div> </figure> </section> <section class="section main-article-chapter" data-menu-title="Benefits of data visualization"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Benefits of data visualization</h2> <p>While data visualization serves many purposes, it also supports several ways organizations interpret and act on data, including:  </p> <ul class="default-list"> <li><b>Actionable insights.</b> BI dashboards and other data visualization tools help people absorb information quickly, gain better insights and take next steps faster.</li> <li><b>Exploration of complex relationships.</b> Modern analytics and visualization platforms reveal complex relationships across many variables to drive more data-based decisions.</li> <li><b>Clear storytelling.</b> Focused visuals and narratives maintain the audience's interest with information they can readily understand.</li> <li><b>Interactivity.</b> Users can drill into the data behind the charts for deeper analysis.</li> </ul> </section> <section class="section main-article-chapter" data-menu-title="Data visualization challenges and disadvantages"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Data visualization challenges and disadvantages</h2> <p>While data visualization is meant to offer clarity, it can introduce certain risks, including:</p> <ul class="default-list"> <li><b>Complexity.</b> Dense visuals obscure data insights. Without visualization training, there's an increased risk that analysts and business users will create cluttered designs or the wrong visual type for the data.</li> <li><b>Misinterpretation.</b> Users might draw incorrect conclusions if visualizations aren't fully clear or if they don't examine the data closely enough.</li> <li><b>Data privacy and security.</b> Organizations face risks related to both the security of data visualization platforms and compliance with data privacy regulations.</li> <li><b>Bias.</b> Visualizations and the data behind them should be scrutinized for signs of bias. Failing to do so could compromise the credibility of the analytics results.</li> <li><b>Environmental impact. </b>Visuals generated with AI often require massive computing power, which can increase energy consumption and affect corporate sustainability goals.</li> </ul> </section> <section class="section main-article-chapter" data-menu-title="Data visualization, AI and big data"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Data visualization, AI and big data</h2> <p>Companies increasingly use machine learning and other AI tools to  process massive amounts of data that can be difficult and time-consuming to sort through and analyze without their help. While these AI-driven analytics applications in big data environments offer new opportunities to present information to stakeholders, they also require new data visualization approaches.</p> <p>Conventional visualizations, such as pie charts, <a href="https://www.techtarget.com/searchsoftwarequality/definition/histogram">histograms</a> and graphs, remain useful for summaries but are limited for large-scale data exploration. For deeper discovery, modern big-data platforms pair advanced visuals -- for example, heat maps and scatter plots -- with cloud-powered AI to automatically highlight trends or new opportunities that might otherwise remain buried in the data. This architecture keeps visual designs fast and clear, even when they're built on massive, streaming data sets.</p> <p>Despite their potential value, data visualization projects on big data platforms have drawbacks, including:</p> <ul class="default-list"> <li><b>Information overload. </b>Complex visualizations can confuse users or lead them to make inaccurate conclusions.</li> <li><b>Technical maintenance. </b>Modern data pipelines require constant maintenance to prevent dashboards from breaking. IT teams must also monitor cloud costs.</li> <li><b>Lack of trust. </b>Without governance and transparency, AI-generated insights are opaque, making it difficult to gain user confidence in them.</li> <li><b>Need for advanced skills. </b>Creating sophisticated visuals requires specialized skills. In addition, business users need data literacy skills to understand complex analytics results.</li> <li><b>Data quality issues. </b>Manually checking data quality in big data systems is not feasible. Organizations need automated tools to identify quality and accuracy issues before data reaches dashboards.</li> <li><b>Hidden bias. </b>Even technically accurate visualizations can mislead users without proper context or when data sample sizes are small.</li> </ul> <div class="youtube-iframe-container"> <iframe id="ytplayer-0" src="https://www.youtube.com/embed/Vy1axaMB980?autoplay=0&modestbranding=1&rel=0&widget_referrer=null&enablejsapi=1&origin=https://www.techtarget.com" type="text/html" height="360" width="640" frameborder="0" loading="lazy"></iframe> </div> </section> <section class="section main-article-chapter" data-menu-title="Examples of data visualization"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Examples of data visualization</h2> <p> Tables, bar charts, pie charts and other traditional data visualization methods are still widely used for their simplicity and accessibility. However, <a href="https://www.techtarget.com/searchbusinessanalytics/feature/8-top-data-science-applications-and-use-cases-for-businesses">data science applications</a> and data storytelling often demand more advanced visualization techniques, such as bullet graphs for tracking performance, heat maps for identifying patterns, bubble charts for analyzing relationships among variables and Sankey diagrams for visualizing flows and processes.</p> <p>Other types of data visualizations that continue to be popular include:</p> <ul class="default-list"> <li><b>Line charts. </b>Among the most basic and widely used techniques, line charts show how variables change over time, making them ideal for trend analysis.</li> <li><b>Area charts. </b>A variation of line charts, area charts fill the space between the x-axis and a line with color or shading. This design shows both how data changes over time and the total volume of the values; different groups of values can also be compared. Some common examples of area charts include tracking population growth or total sales over a specific time period.  </li> <li><b>Treemaps. </b>As the name suggests, treemaps use a tree-like structure to show hierarchical data and how the parts add up to the whole through nested and often color-coded rectangles. The space-filling design reveals patterns or outliers in complex data sets. One example of a treemap is a company's entire budget broken down by department, using different-sized rectangles to show the percentage given to each department.</li> <li><b>Scatter plots. </b>This type of chart shows the relationship between two different variables. Each observation is represented by a dot placed on the chart based on its values for the two variables: one on the x-axis and the other on the y-axis. Scatter plots are helpful to find patterns in data, such as correlations and outliers. For example, a scatter plot can show the connection between the number of hours studied on the x-axis and final test scores on the y-axis; an upward trend would indicate that more studying is associated with higher test scores.</li> <li><b>Population pyramids. </b>These use back-to-back bar charts to display a population's distribution by age, sex and other characteristics. They can show trends that identify demographic shifts driven by events, such as mass migrations or health crises. Business uses include analyzing spending by customer groups, planning retail locations and tracking workforce demographics.</li> </ul> </section> <section class="section main-article-chapter" data-menu-title="Common data visualization use cases"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Common data visualization use cases</h2> <p>Across industries, teams use data visualization to see what has changed, why it changed and what to do next.</p> <ul class="default-list"> <li><b>Sales and marketing. </b>Interactive dashboards track real-time sales performance. Trend lines show customer engagement. Comparative charts highlight marketing campaigns with the highest ROI. Modern analytics platforms integrate AI to provide predictive forecasting that helps marketers anticipate future trends and optimize budget allocation.</li> <li><b>Healthcare. </b>Choropleth maps show health indicators across regions, such as heart disease mortality rates by state or county, to highlight geographic disparities. These visualizations help healthcare organizations and public health officials identify areas that require more resources. Hospitals also use data visualizations to help diagnose medical conditions and track patient treatments and outcomes.</li> <li><b>Financial services.</b> Finance professionals rely on data visualization to track asset performance and decide when to execute trades. Candlestick charts are the industry standard for visualizing price movements within a specified time frame to show market trends and reactions. In addition, visualized data helps banks analyze credit risks and customer portfolios.</li> <li><b>Insurance.</b> Insurers similarly use data visualizations to analyze policy risks and pricing when customers apply for coverage.</li> <li><b>Manufacturers.</b> Data visualization helps them plan production, monitor manufacturing operations and manage inventories of materials and supplies.</li> <li><b>Logistics. </b>Route optimization dashboards combine real-time data on traffic, weather and inventory to pinpoint the fastest and most cost-effective distribution paths. These visualizations help logistics organizations reduce delivery times, save on fuel costs and better manage their vehicle fleets.</li> <li><b>Travel.</b> Airlines use visualizations of data on ticket sales and flight occupancy rates to adjust flight schedules and plan crew assignments. Similarly, hotel chains track room occupancy and pricing data to guide marketing campaigns and promotions aimed at maximizing bookings.</li> <li><b>Politics. </b>A bivariate choropleth map visualizes voting patterns with demographic overlays showing income or education levels. Time series charts track trends in polling numbers and campaign fundraising to help politicians determine where their messaging yields the most results.</li> <li><b>Scientific research.</b> Scientific visualization turns complex data from experiments and other data collection initiatives into high-dimensional charts and 3D models. These provide researchers with clearer ways to present scientific findings, such as molecular structures or atmospheric changes.</li> </ul> </section> <section class="section main-article-chapter" data-menu-title="The science of data visualization"> <h2 class="section-title"><i class="icon" data-icon="1"></i>The science of data visualization</h2> <p>Data visualization is grounded in how humans process information. Psychologist Daniel Kahneman, building on decades of collaborative research with colleague Amos Tversky, defined the concept of two systems of thinking in his book <i>Thinking, Fast and Slow</i>:</p> <ul class="default-list"> <li><b>System 1 (fast thinking).</b> Quick, automatic and intuitive processing that requires little conscious effort. We use it for everyday tasks, such as reading a sign, solving simple math problems, detecting aggression in voices and distinguishing between colors.</li> <li><b>System 2 (slow thinking).</b> Deliberate and logical processing that requires intentional mental engagement. This system is used for more involved tasks, such as solving complex math problems, preparing tax forms and parking in a tight space.</li> </ul> <p>Research published by MIT in 2025 shows that data visualization design choices convey social meaning and can shape levels of trust before people even check the data. For example, the MIT researchers found that highly polished data visualizations were often perceived as promotional and less trustworthy, whereas plain designs were perceived as more objective. The researchers suggested that designers must account for both cognitive processing and social meaning when creating data visualizations.</p> </section> <section class="section main-article-chapter" data-menu-title="Data visualization tools and vendors"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Data visualization tools and vendors</h2> <p>In the past, data visualization was often limited to using Microsoft Excel to convert spreadsheet data into tables and charts. Modern <a href="https://www.techtarget.com/searchbusinessanalytics/feature/Top-business-intelligence-tools-to-know-about">BI and analytics platforms</a>, such as Looker Studio, Power BI, Qlik Sense and Tableau, and open-source visualization libraries, such as D3, Matplotlib and Plotly, have transformed data visualization. These tools connect to governed cloud data to prepare it for analysis, then deliver interactive dashboards, reports, alerts and AI-generated insights.</p> <p>Many now have a variety of AI features, such as automated trend detection, <a href="https://www.techtarget.com/whatis/definition/natural-language-query">natural language querying</a> and predictive analytics driven by machine learning. Tools with generative AI capabilities, such as Tableau Pulse and Power BI Copilot, tell users what has changed in data sets and why.</p> <p>BI and data visualization tools typically integrate directly with cloud data platforms, such as Google BigQuery, Snowflake, Databricks and Microsoft Fabric's OneLake. This architecture gives users a way to explore governed data in a unified environment that ensures KPI definitions are consistent across their organization.</p> <p>For guidance on tool purchases, buyers can consult the vendor rankings and analysis in Gartner Magic Quadrant and Forrester Wave reports on BI platforms. Some notable vendors listed in the 2025 versions of those reports include AWS, Domo, Google, Microsoft, Oracle, Qlik, ThoughtSpot and Salesforce, which owns Tableau.</p> </section> <section class="section main-article-chapter" data-menu-title="New and emerging trends in data visualization"> <h2 class="section-title"><i class="icon" data-icon="1"></i>New and emerging trends in data visualization</h2> <p>Leaders want answers quickly, so visualization is moving from passive to active thanks to these technological advances.</p> <ul class="default-list"> <li><b>AI</b><b>‑driven visualization. </b>Tools now turn natural language queries into charts and dashboards. This shift toward on-the-fly visual creation speeds up results for business leaders who would otherwise wait for data analysts to provide answers.</li> <li><b>Augmented analytics.</b> Tools automatically detect issues and trends, explaining them with quick visuals, so teams can act faster. Recent research from analysts and business schools finds that more enterprises are deploying agent‑style assistants that use governance as the guardrail to ensure answers are trustworthy.</li> <li><b>Real</b><b>‑time streaming dashboards. </b>Users can watch live KPIs with continuous updates rather than a daily refresh. As needed, they can click into a metric to see details and set rules, such as triggering an alert via Microsoft Teams when a threshold is crossed. This avoids the need for multiple tools and speeds response in areas such as <a href="https://www.techtarget.com/iotagenda/definition/Internet-of-Things-IoT">IoT</a> monitoring, fraud detection and logistics tracking.</li> <li><b>Immersive visualization.</b> Augmented reality and virtual reality technologies help users <a target="_blank" href="https://www.nist.gov/information-technology/extended-reality" rel="noopener">explore</a> 3D or spatial data when static charts hide key relationships, such as factory layouts and geospatial routes. AR/VR lets teams inspect data at true scale, toggle layers and capture context for design reviews and fieldwork.</li> </ul> <p><i>Data visualization is a subset of the broader concept of data analytics. Learn the different ways in which </i><a href="https://www.techtarget.com/searchbusinessanalytics/tip/366542263/8-ways-to-drive-business-value-with-advanced-analytics"><i>advanced analytics tools drive business value</i></a><i>.</i></p> <p><i>Former TechTarget editors Cameron Hashemi-Pour, Kate Brush and Ed Burns also contributed to this article.</i></p> </section> Data visualization translates information into charts, maps or other graphics to show patterns, trends and outliers in a way that can be grasped quickly. https://cdn.ttgtmedia.com/visuals/digdeeper/1.jpg https://www.techtarget.com/searchbusinessanalytics/definition/data-visualization Tue, 17 Feb 2026 09:15:00 GMT What is data visualization? <p>A data scientist is an analytics professional who collects, analyzes and interprets data to transform it into <a href="https://www.techtarget.com/searchcustomerexperience/definition/actionable-insights">actionable insights</a> that can facilitate decision-making. The data scientist's makes sense of large amounts of raw data to help answer questions and mitigate business challenges.</p> <p>The data scientist role merges several traditional and technical jobs, including mathematician, scientist, statistician and programmer. The work uses advanced analytics, such as <a href="https://www.techtarget.com/searchenterpriseai/tip/AI-vs-machine-learning-vs-deep-learning-Key-differences">machine learning</a> and <a href="https://www.techtarget.com/searchsoftwarequality/tip/How-to-test-a-predictive-model">predictive modeling</a>, and applying mathematical and scientific principles to collect, process, analyze and interpret data.</p> <p>The data scientist job title emerged in 2008 on various social media sites; four years later, a <i>Harvard Business Review </i><a target="_blank" href="https://hbr.org/2012/10/data-scientist-the-sexiest-job-of-the-21st-century" rel="noopener">article</a> called it "the sexiest job of the 21st century."</p> <p><a href="https://www.techtarget.com/searchbusinessanalytics/feature/The-most-in-demand-data-science-skills-you-need"></a>Demand for data science skills has grown as companies seek useful information from massive volumes of <a href="https://www.techtarget.com/searchdatamanagement/feature/Top-trends-in-big-data-for-2021-and-beyond">big data</a>, and hope to harness artificial intelligence (AI) and machine learning technologies in new types of analytics applications. As data volumes explode, many organizations now rely on data scientists to interpret data and present it in an actionable form.</p> <section class="section main-article-chapter" data-menu-title="What does a data scientist do?"> <h2 class="section-title"><i class="icon" data-icon="1"></i>What does a data scientist do?</h2> <p>In business settings, data scientists typically <a href="https://www.techtarget.com/searchbusinessanalytics/definition/data-mining">mine data</a> for information used to predict customer behavior, identify revenue opportunities, detect fraudulent transactions and meet other business needs. They support organizations in a range of industries and sectors, including finance, healthcare, telecommunications, technology, media and entertainment, government, utilities and law enforcement.</p> <p>Data scientists work on <a href="https://www.techtarget.com/searchenterpriseai/definition/data-science"></a>initiatives that use large amounts of data to develop and test hypotheses, make inferences and analyze areas such as markets, financial risks, <a href="https://www.techtarget.com/searchsecurity/feature/How-AI-threat-detection-is-transforming-enterprise-cybersecurity">cybersecurity threats</a>, stock trades, equipment maintenance needs and medical conditions. They use mathematical and statistical techniques, computer science and machine learning capabilities, and their understanding a business or industry to uncover useful and actionable insights, patterns and trends from the data.</p> <p>Data scientists are commonly tasked with finding and interpreting information that enables better marketing campaigns, customer service, <a href="https://www.techtarget.com/searcherp/Guide-to-supply-chain-management">supply chain management</a>, and business decisions and strategies. They do this by analyzing sets of quantitative and qualitative data, depending on the needs of specific applications and organizations.</p> <p>Sometimes, data scientists explore data without being given a specific business problem to solve. In these scenarios, they must understand both the data and the business well enough to formulate questions, generate hypotheses, do the analysis and deliver insights to business executives on ways to improve business operations, products or services.</p> <p>In many organizations, data scientists are responsible for helping to define and promote best practices for data collection, preparation and analysis. Some data scientists develop AI technologies for internal use or for customers. These can be conversational AI systems, AI-driven robots and other autonomous machines, including key components in <a href="https://www.computerweekly.com/news/366626435/Autonomous-vehicle-technology-market-set-to-roll">self-driving cars</a>.</p> <p>In general, the basic responsibilities of a data scientist include the following:</p> <ul class="default-list"> <li>Gathering and preparing relevant data to use in analytics applications.</li> <li>Using various analytics tools to detect patterns, trends and relationships in data sets.</li> <li>Cleaning and integrating data, and then loading it into a data warehouse, data lake or other storage repository.</li> <li>Developing statistical and predictive models to run against the data sets.</li> <li>Creating <a href="https://www.techtarget.com/searchbusinessanalytics/definition/data-visualization">data visualizations</a>, dashboards and reports to communicate findings to decision-makers.</li> </ul> <p>Data scientists typically present their insights  to decision-makers and other stakeholders as reports, stories, illustrations and other visualizations that show what the data means in nontechnical terms. This helps end users understand the data and use it to inform strategic planning, problem-solving and decision-making.</p> <p>Besides analyzing data to glean insights, data scientists also handle the following tasks:</p> <ul class="default-list"> <li>Collecting and extracting <a href="https://www.techtarget.com/whatis/feature/Structured-vs-unstructured-data-The-key-differences">structured and unstructured data</a> from various sources using methods like scraping, manual data entry and real-time data streaming.</li> <li>Improving data quality by cleaning, deduplicating or combining it.</li> <li>Creating data models  for predictive analytics and machine learning.</li> <li>Configuring and implementing data analysis tools.</li> <li>Writing algorithms to automate data processing.</li> </ul> <div class="youtube-iframe-container"> <iframe id="ytplayer-0" src="https://www.youtube.com/embed/F1ZpufU-DMY?autoplay=0&modestbranding=1&rel=0&widget_referrer=null&enablejsapi=1&origin=https://www.techtarget.com" type="text/html" height="360" width="640" frameborder="0" loading="lazy"></iframe> </div> </section> <section class="section main-article-chapter" data-menu-title="Characteristics of an effective data scientist"> <h2 class="section-title"><i class="icon" data-icon="1"></i><a href="https://www.techtarget.com/searchbusinessanalytics/feature/8-top-data-science-applications-and-use-cases-for-businesses"></a><a href="https://www.techtarget.com/searchbusinessanalytics/definition/data-visualization"></a>Characteristics of an effective data scientist</h2> <p>Data scientists should have certain traits and skills that include the following:</p> <ul class="default-list"> <li>Intellectual curiosity.</li> <li>Critical thinking.</li> <li>A healthy skepticism.</li> <li>Good intuition.</li> <li>Problem-solving abilities.</li> <li>Creativity.</li> </ul> <p>Data scientists typically work on a data science team that includes data engineers and data analysts.</p> <p>Since they frequently communicate with diverse audiences, interpersonal skills and the ability to work well with others are critical requirements. Data scientists should be strong communicators who can <a href="https://www.techtarget.com/searchbusinessanalytics/feature/How-to-enhance-your-data-science-storytelling">use data storytelling capabilities</a> to present and explain data insights to executives, managers and other employees. They need leadership capabilities and business savvy to understand the organization and its data requirements, and to help steer a <a href="https://www.techtarget.com/searchbusinessanalytics/tip/Key-steps-form-a-data-driven-decision-making-framework">data-driven decision-making</a> process.</p> <figure class="main-article-image full-col" data-img-fullsize="https://www.techtarget.com/rms/onlineimages/business_analytics-data_science_team_org_chart-f.png"> <img data-src="https://www.techtarget.com/rms/onlineimages/business_analytics-data_science_team_org_chart-f_mobile.png" class="lazy" data-srcset="https://www.techtarget.com/rms/onlineimages/business_analytics-data_science_team_org_chart-f_mobile.png 960w,https://www.techtarget.com/rms/onlineimages/business_analytics-data_science_team_org_chart-f.png 1280w" alt="An organization chart for a data science team with the types of roles normally included." height="569" width="559"> <figcaption> <i class="icon pictures" data-icon="z"></i>A data science team has a variety of roles, including data scientists, data analysts and data architects. </figcaption> <div class="main-article-image-enlarge"> <i class="icon" data-icon="w"></i> </div> </figure> </section> <section class="section main-article-chapter" data-menu-title="Technical skills and qualifications"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Technical skills and qualifications</h2> <p>Data scientists process and analyze data, and then uncover actionable insights. They must be able to complete a range of complex planning, modeling and analytical tasks in a timely manner. These requirements dictate that data scientists have mastery of the following skills:</p> <ul class="default-list"> <li><a href="https://www.techtarget.com/searchbusinessanalytics/feature/15-data-science-tools-to-consider-using">Data science tools</a> and libraries.</li> <li>Interactive development tools, like Jupyter Notebook and GitHub.</li> <li>Big data platforms, such as Hadoop, Hive, Kafka and Spark.</li> <li>Statistical analysis tools like SAS and IBM SPSS.</li> <li>Programming languages, such as Julia, Python, R, Scala and SQL.</li> </ul> <p>Technical skills required include data mining, predictive modeling, machine learning, <a href="https://www.techtarget.com/searchenterpriseai/definition/deep-learning-deep-neural-network">deep learning</a>, upfront data processing and <a href="https://www.techtarget.com/searchbusinessanalytics/definition/data-preparation">data preparation</a>. The ability to work with structured, semistructured and unstructured data is required, especially in big data environments with different types of data. Data scientists usually have experience with statistical research and analytics techniques, such as classification, clustering, regression and segmentation. Expertise in natural language processing (<a href="https://www.techtarget.com/searchenterpriseai/definition/natural-language-processing-NLP">NLP</a>) is another prerequisite.</p> <p>Data scientist job postings typically call for the following skills and experience:</p> <ul class="default-list"> <li>Expertise in all phases of data science, from initial data discovery through <a href="https://www.techtarget.com/searchdatamanagement/tip/The-difference-between-data-cleansing-and-data-transformation">data cleansing</a> and model selection, validation and deployment.</li> <li>Knowledge and understanding of common <a href="https://www.techtarget.com/searchdatamanagement/feature/Beyond-the-RDBMS-Data-warehouse-vs-data-lake-vs-data-mart">data warehouse and data lake structures</a>.</li> <li>Experience with using statistical approaches to solve analytics problems.</li> <li>Proficiency in machine learning frameworks.</li> <li>Familiarity with common <a href="https://www.techtarget.com/searchbusinessanalytics/feature/15-common-data-science-techniques-to-know-and-use">data science and machine learning techniques</a>, such as decision trees, K-nearest neighbors, naive Bayes classifiers, random forests and support vector machines.</li> <li>Experience with techniques for qualitative and quantitative analysis.</li> <li>The ability to identify new opportunities to apply machine learning and data mining tools to business processes for optimal efficiency and effectiveness.</li> <li>Experience with public cloud platforms and services.</li> <li>Familiarity with data sources, including databases and big data platforms, as well as public and private APIs and standard data formats, like JSON, YAM and XML.</li> <li>The ability to aggregate data from disparate sources and prepare it for analysis.</li> <li>Experience with data visualization tools, such as Microsoft's Power BI and Salesforce's Tableau.</li> <li>The ability to design and implement reporting dashboards that can track key business metrics and provide actionable insights.</li> <li>The ability to do ad hoc analysis and present the results in a clear manner.</li> </ul> <figure class="main-article-image full-col" data-img-fullsize="https://www.techtarget.com/rms/onlineImages/business_analytics-data_whisperer.jpg"> <img data-src="https://www.techtarget.com/rms/onlineImages/business_analytics-data_whisperer_mobile.jpg" class="lazy" data-srcset="https://www.techtarget.com/rms/onlineImages/business_analytics-data_whisperer_mobile.jpg 960w,https://www.techtarget.com/rms/onlineImages/business_analytics-data_whisperer.jpg 1280w" alt="Attributes of successful data scientists" height="731" width="520"> <figcaption> <i class="icon pictures" data-icon="z"></i>These are the key personal and professional attributes that a data scientist should have. </figcaption> <div class="main-article-image-enlarge"> <i class="icon" data-icon="w"></i> </div> </figure> </section> <section class="section main-article-chapter" data-menu-title="Education, training and certifications"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Education, training and certifications</h2> <p>Most data science jobs require a bachelor's degree in data science or a related technical field. Many data scientists have advanced degrees in statistics, data science, computer science or mathematics. Candidates must have a basic understanding of the key concepts from these fields. Knowledge of concepts from other fields, like machine learning, deep learning, NLP and analytics, is preferred.</p> <p>3Prospective and experienced data scientists looking to show readiness for a job in the field can take advantage of boot camps and online courses that educational platforms such as Codecademy, Coursera, Kaggle and Udemy offer. Many universities have data science courses. For example, UC Berkeley offers the following courses:</p> <ul class="default-list"> <li>Foundations of data science.</li> <li>Computational structures in data science.</li> <li>Principles and techniques of data science.</li> <li>Data engineering.</li> <li>Data mining and analytics.</li> <li>Probability for data science.</li> <li>Data and justice.</li> </ul> <p><a href="https://www.techtarget.com/whatis/feature/Top-25-Data-Science-Certification-Courses">Various certification opportunities</a> for beginners and experienced professionals are available through universities, technology vendors and industry groups. IBM offers a beginner-level Data Science Professional Certificate. Harvard University offers an introductory Professional Certificate in Data Science. The Data Science Council of America offers numerous globally recognized certifications for data scientists at all career levels.</p> <p>Organizations can implement internal programs to train talented and interested professionals working in other positions or fields to become data scientists. Those employees might include database developers and software programmers, as well as traditional scientists and other experts in particular disciplines.</p> </section> <section class="section main-article-chapter" data-menu-title="Data scientist salaries"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Data scientist salaries</h2> <p>Because the desired combination of analytics skills, personality traits and experience is still somewhat elusive, qualified data scientists can command high salaries. According to job posting site Indeed, the average base salary for data scientists in the U.S. in late 2025 was nearly $130,000, based on about 4,800 reported salaries. The high end of the range reported was nearly $208,000.</p> <p>The U.S. Bureau of Labor Statistics (BLS) predicts the outlook for data scientist jobs is positive. In 2024, 245,900 such jobs were added to the U.S. economy. The BLS predicts this job category will grow 34% in the next decade, much faster than the average for all occupations.</p> </section> <section class="section main-article-chapter" data-menu-title="Data scientist vs. data analyst"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Data scientist vs. data analyst</h2> <p>The role of data scientist is <a href="https://www.techtarget.com/searchbusinessanalytics/infographic/Data-scientist-vs-data-analyst-A-visual-breakdown">often confused with that of data analyst</a>. While there is overlap in many of the job responsibilities and required skills, there are significant differences.</p> <p>A data analyst's duties can vary . They collect, process and analyze data, and also create visualizations and dashboards to report findings. Some data analysts design and maintain the databases and other data stores used in analytics applications. Generally, they don't have all the technical skills required of the data scientist. They can also lack the business acumen and industry-level understanding data scientists need.</p> <p>Data analysts often support the work of data scientists and report to a data scientist when working on analytics initiatives. Since data analysts have fewer responsibilities, they often earn less than data scientists – about $84,000 on average in the U.S. in 2025 vs. nearly $130,000 for a data scientist, according to Indeed.</p> </section> <section class="section main-article-chapter" data-menu-title="Data scientists vs. citizen data scientist"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Data scientists vs. citizen data scientist</h2> <p>In addition to skilled data scientists, many organizations rely on <a href="https://www.techtarget.com/searchbusinessanalytics/definition/citizen-data-scientist">citizen data scientists</a> to do some analytics work. They can include business intelligence (<a href="https://www.techtarget.com/searchbusinessanalytics/definition/business-intelligence-BI">BI</a>) professionals, business analysts, data-savvy business users and other workers who get involved in data science initiatives. The differences between the two groups include the following:</p> <ul class="default-list"> <li><b>Education.</b> Data scientists have relevant degrees, while citizen data scientists have a variety of educational backgrounds and little or no formal training in data science. Typically, they've gained enough experience with analytics tools and systems to create models and do relatively complex analysis work.</li> <li><b>Coding.</b> Citizen data scientists rely on software that includes prebuilt analytical modeling tools, drag-and-drop features and user-friendly algorithms to perform standard analyses. That doesn't prevent them from discovering patterns or data points, but professional data scientists can create complex custom algorithms and approach data analysis in more advanced ways.</li> <li><b>Salary.</b> Citizen data scientists earn less than data scientists. Although some get additional compensation for data science work, most do not.</li> <li><b>Tools.</b> The range and complexity of tools used for the roles differ. Data scientists use data science tools with built-in statistical modeling or machine learning capabilities, programming languages, data visualization tools, data processing platforms, databases and machine learning frameworks. BI professionals use BI tools to prepare, mine, manage and analyze data. These tools help them visualize data, identify actionable information and generate descriptive insights to support decision-making.</li> </ul> </section> <section class="section main-article-chapter" data-menu-title="Major areas of data science work"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Major areas of data science work</h2> <p>The key aspects of a data scientist's job include the following disciplines:</p> <ul class="default-list"> <li><b>Data preparation.</b> The first step in data science applications is to collect and prepare the data to be analyzed. This involves gathering, cleansing, organizing, transforming and validating data sets. Data scientists often <a href="https://www.techtarget.com/searchbusinessanalytics/feature/Key-differences-of-a-data-scientist-vs-data-engineer">work with data engineers</a> in the data prep phase.</li> <li><b>Data analytics.</b> The analytics work of data scientists is aimed at improving business performance and helping organizations gain a competitive advantage.</li> <li><b>Data mining.</b> Advanced algorithms are applied to the data being analyzed. Data scientists use the results algorithms generate to create analytical models and uncover patterns and relationships in large data sets.</li> <li><b>Machine learning.</b> Increasingly, machine learning drives data mining and analytics. Algorithms are built to learn about data sets and then find the desired information in them. Data scientists are responsible for <a href="https://www.techtarget.com/searchenterpriseai/feature/5-types-of-machine-learning-algorithms-you-should-know">training and overseeing machine learning algorithms</a> as needed. Deep learning is a more advanced form that uses artificial neural networks.</li> <li><b>Predictive modeling.</b> Data scientists must be able to create predictive models of different business scenarios to analyze potential outcomes. Models can be built to predict how different customers will respond to marketing offers or to assess possible indicators of diseases.</li> <li><b>Statistical analysis.</b> Data science work also involves using statistical analysis techniques to analyze data sets. This is a way to explore data and find and interpret trends and patterns.</li> <li><b>Data visualization.</b> Findings from data science applications are usually organized into <a href="https://www.techtarget.com/searchbusinessanalytics/tip/12-data-visualization-techniques-for-effective-BI-applications">charts or other visualizations</a> so target audiences can easily understand them. Often, data scientists combine multiple visualizations into reports, interactive dashboards or detailed data stories.</li> </ul> </section> <section class="section main-article-chapter" data-menu-title="Challenges that data scientists face"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Challenges that data scientists face</h2> <p>Despite having what's seen as one of the best IT jobs, data scientists face challenges. Their work is complex, and because they often aren't given specific questions to answer or research areas to focus on, data scientists can't always be sure that what they do will meet business needs.</p> <figure class="main-article-image half-col" data-img-fullsize="https://www.techtarget.com/rms/onlineimages/enterprise_ai-data_science_challenges-h.png"> <img data-src="https://www.techtarget.com/rms/onlineimages/enterprise_ai-data_science_challenges-h_half_column_mobile.png" class="lazy" data-srcset="https://www.techtarget.com/rms/onlineimages/enterprise_ai-data_science_challenges-h_half_column_mobile.png 960w,https://www.techtarget.com/rms/onlineimages/enterprise_ai-data_science_challenges-h.png 1280w" alt="Common data science challenges" height="306" width="279"> <figcaption> <i class="icon pictures" data-icon="z"></i> Data scientists regularly contend with these challenges, according to Gartner. </figcaption> <div class="main-article-image-enlarge"> <i class="icon" data-icon="w"></i> </div> </figure> <p>Gathering relevant data for analytics applications can be difficult, especially in organizations with <a href="https://www.techtarget.com/searchdatamanagement/definition/data-silo">data silos</a>. Incorrect or inconsistent data can skew results. To avoid that, rigorous data profiling and cleansing is required upfront to identify and fix data quality issues.</p> <p>Data preparation is time-consuming: Data scientists spend 80% of their time finding and preparing data and only 20% analyzing it. This results in inefficient use of the data scientist's time and abilities, which impede on-time project completion and other outcomes.</p> <p>Identifying and addressing <a href="https://www.techtarget.com/searchbusinessanalytics/feature/8-types-of-bias-in-data-analysis-and-how-to-avoid-them">biases in data science applications</a> is a challenge, both in the data being analyzed and in algorithms and analytical models. Maintaining models and ensuring that they're updated when data sets or business requirements change can be problematic. Finally, analytics workloads can be hard to handle if companies don't invest in a full data science team.</p> </section> A data scientist is an analytics professional who collects, analyzes, and interprets data to transform it into actionable insights that can facilitate decision-making. https://cdn.ttgtmedia.com/visuals/digdeeper/5.jpg https://www.techtarget.com/searchenterpriseai/definition/data-scientist Tue, 23 Dec 2025 23:15:00 GMT What is a data scientist? What do they do? <p>Fifth-generation wireless or 5G is a global standard and technology for wireless and telecommunications networks. It uses radio waves to transmit data, just like the previous wireless standards 3G, <a href="https://www.techtarget.com/searchmobilecomputing/definition/4G">4G</a> and 4G Long-Term Evolution (<a href="https://www.techtarget.com/searchmobilecomputing/definition/Long-Term-Evolution-LTE">LTE</a>). Compared to its predecessors, 5G offers significant improvements in bandwidth, speed and <a href="https://www.techtarget.com/whatis/definition/latency">latency</a>.</p> <p>Engineered to operate on higher frequencies, 5G significantly enhances the speed and bandwidth of wireless networks while reducing latency compared to older wireless networks. 5G is also more reliable and offers stronger connectivity compared to earlier standards.</p> <p>These advances are crucial for addressing the <a target="_blank" href="https://datareportal.com/reports/digital-2025-global-overview-report" rel="noopener">growing demand</a> for internet access worldwide. In early 2025, 67.9% of the global population used the internet, according to the <i>Digital 2025: Global Overview Report</i> by research organization DataReportal. That's 5.56 billion internet users out of a global population of 8.2 billion – an increase of 136 billion people compared with 2024.</p> <p>5G is also critical to support the growing amount of data being created worldwide. Per <a target="_blank" href="https://explodingtopics.com/blog/data-generated-per-day" rel="noopener">research</a> and trend analysis firm Exploding Topics, this figure has increased by a staggering 74 times from just 2 zettabytes (ZB) in 2010 to 120 ZB in 2023. Moreover, the upward growth trajectory is expected to continue. For example, 181 ZB of data is expected to be created in 2025. This represents a massive 150% increase over the amount created just two years prior.</p> <p>The network infrastructure of previous wireless networks cannot handle these data volumes. 5G uses infrastructure that offers much higher data capacity and can handle large amounts of data. The higher bandwidth, upload and download speeds, and lower latency of 5G make it better suited than older networks for newer technologies like AI, machine learning (<a href="https://www.techtarget.com/searchenterpriseai/definition/machine-learning-ML">ML</a>) and smart devices, including smartphones, smart speakers, smart home appliances and <a href="https://www.techtarget.com/searchmobilecomputing/definition/wearable-technology">wearables</a>.</p> <p>Currently, 5G is ideal for telecommunications, video streaming, internet of things (<a href="https://www.techtarget.com/iotagenda/definition/Internet-of-Things-IoT">IoT</a>) and industrial IoT (<a href="https://www.techtarget.com/iotagenda/definition/Industrial-Internet-of-Things-IIoT">IIoT</a>), and for private networks using <a href="https://www.techtarget.com/searchnetworking/definition/private-5G">private 5G</a>. It currently supports applications such as self-driving cars, traffic management, smart utilities and supply chain management.</p> <section class="section main-article-chapter" data-menu-title="How does 5G work?"> <h2 class="section-title"><i class="icon" data-icon="1"></i>How does 5G work?</h2> <p>As with 3G and 4G networks, 5G wireless networks are <a href="https://www.techtarget.com/searchnetworking/feature/Macrocell-vs-small-cell-vs-femtocell-A-5G-introduction">composed of cell sites</a> divided into sectors that send data through radio waves. Essentially, cells refer to the smaller, geographical sections that collectively form a 5G service area. 5G devices within a cell use radio waves to connect to the phone network and the internet.</p> <figure class="main-article-image full-col" data-img-fullsize="https://www.techtarget.com/rms/onlineImages/telecom_5G_features.jpg"> <img data-src="https://www.techtarget.com/rms/onlineImages/telecom_5G_features_mobile.jpg" class="lazy" data-srcset="https://www.techtarget.com/rms/onlineImages/telecom_5G_features_mobile.jpg 960w,https://www.techtarget.com/rms/onlineImages/telecom_5G_features.jpg 1280w" alt="A chart listing six features of 5G." height="258" width="560"> <figcaption> <i class="icon pictures" data-icon="z"></i>The biggest benefits of 5G are its potential speed and low latency. </figcaption> <div class="main-article-image-enlarge"> <i class="icon" data-icon="w"></i> </div> </figure> </section> <section class="section main-article-chapter" data-menu-title="Core components of 5G"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Core components of 5G</h2> <p>A base station and antennae facilitate connections over 5G networks. Other core components of 5G include the following:</p> <ul class="default-list"> <li>5G New Radio (<a href="https://www.techtarget.com/whatis/definition/5G-New-Radio-NR">5G NR</a>), which defines the frequency spectrum or bands, in the Sub-7 gigahertz (GHz) range and frequency bands above 24 GHz over which devices connect to the internet to send and receive data.</li> <li>5G Next Generation Core, the element that uses a service-based architecture to facilitate control and management of the 5G network and devices connected to it.</li> <li>Multi-access edge computing, which enables the low latency and bandwidth efficiency capabilities of 5G.</li> <li>IP Multimedia Subsystem, which enables the delivery of Internet Protocol-based, rich multimedia services over 5G.</li> </ul> <p>A 5G NR air interface design, which acts as a specification for 5G networks, enables 5G. It describes how 5G products transmit data with 5G NR network infrastructure. 5G uses orthogonal frequency-division multiple access (<a href="https://www.techtarget.com/searchnetworking/definition/orthogonal-frequency-division-multiple-access-OFDMA">OFDMA</a>), the same radio access technology that 4G LTE networks use. In this way, 4G LTE wireless technology is foundational for 5G. Techniques such as <a href="https://www.techtarget.com/searchnetworking/definition/QAM">quadrature amplitude modulation</a>, <a href="https://www.techtarget.com/searchnetworking/definition/beamforming">beamforming</a>, and other advanced features also help 5G enhance network efficiency and reduce latency.</p> </section> <section class="section main-article-chapter" data-menu-title="What is the 5G spectrum?"> <h2 class="section-title"><i class="icon" data-icon="1"></i>What is the 5G spectrum?</h2> <p>The 5G spectrum is divided into millimeter wave (<a href="https://www.techtarget.com/searchnetworking/definition/millimeter-wave-MM-wave">mmWaves</a>) high-band and Sub-6 5G low- and mid-bands. <a href="https://www.computerweekly.com/news/366628281/Low-band-spectrum-indispensable-to-5G-evolution">Low-band frequencies</a> are the slowest of 5G speeds but are still faster than some 4G LTE speeds. Mid-band, by comparison, is faster than low-band, but is still eclipsed by mmWave. Sub-6 5G reaches greater distances than mmWave, but has lower speed and capacity compared to mmWave. Although Sub-6 5G is slower than mmWave, it is typically still faster than average 4G LTE speeds.</p> <p>In densely populated areas, mmWave remains in use, while Sub-6 frequencies can be used in less dense areas. The lower-end frequencies can travel up to hundreds of square miles. This means that implementing all 5G frequency bands provides comprehensive coverage and the fastest speeds in the most heavily trafficked areas.</p> </section> <section class="section main-article-chapter" data-menu-title="The importance of mmWave spectrum in 5G"> <h2 class="section-title"><i class="icon" data-icon="1"></i>The importance of mmWave spectrum in 5G</h2> <p>Unlike 4G, which requires large, high-power cell towers to radiate signals over longer distances, 5G wireless signals travel through many small cell stations, such as those located on light poles or building roofs. The use of multiple small cells is necessary, as the <a href="https://www.techtarget.com/searchnetworking/definition/millimeter-wave-MM-wave"></a>mmWave spectrum -- the band 5G relies on to generate high speeds -- can only travel over short distances and is subject to interference from weather and physical obstacles.</p> <p>Trees, walls and buildings can easily block mmWave frequencies. Often, mmWave can only cover about a city block within the direct line of sight of a cell site or node. Different workarounds have been tried. A brute-force approach involves using multiple nodes around each block of a populated area so a 5G-enabled device can use an air interface -- switching from node to node while maintaining mmWave speeds. Another, more feasible, way of offsetting the <a href="https://www.techtarget.com/searchnetworking/tip/Top-5G-limitations-for-businesses-include-lack-of-range-devices">challenges relating to distance</a> and interference with mmWave is using it in conjunction with a lower frequency wireless spectrum -- called Sub-6 5G. The Sub-6 5G spectrum is superior to mmWave in terms of distance supported, but inferior in terms of speed and capacity.</p> </section> <section class="section main-article-chapter" data-menu-title="How fast is 5G?"> <h2 class="section-title"><i class="icon" data-icon="1"></i>How fast is 5G?</h2> <p>With 5G, data transmitted over <a href="https://www.techtarget.com/searchmobilecomputing/definition/wireless-broadband">wireless broadband</a> connections can travel at multigigabit speeds, with potential ideal peak download speeds as high as 20 gigabits per second (Gbps). These speeds surpass wireline network speeds and can offer latency of under 5 milliseconds (ms), which is beneficial for applications that require real-time feedback or uninterrupted internet connectivity. 5G enables a sharp increase in the amount of data transmitted over wireless systems due to more available bandwidth and advanced antenna technology.</p> <p>Each band in the 5G spectrum operates at different speeds:</p> <ul class="default-list"> <li>Low bands provide speeds less than 1 GHz, but are still faster than some 4G LTE speeds.</li> <li>Mid-band provides speeds from 3.4 GHz to 6 GHz.</li> <li>The mmWave band is 30 GHz to 300 GHz.</li> </ul> <p>Each band's speed varies depending on factors such as the carrier, distance, amount of traffic on the network, or obstacles in the case of mmWaves.</p> <figure class="main-article-image full-col" data-img-fullsize="https://www.techtarget.com/rms/onlineimages/networking-compare_cellular_vs_millimeter_wave-f.png"> <img data-src="https://www.techtarget.com/rms/onlineimages/networking-compare_cellular_vs_millimeter_wave-f_mobile.png" class="lazy" data-srcset="https://www.techtarget.com/rms/onlineimages/networking-compare_cellular_vs_millimeter_wave-f_mobile.png 960w,https://www.techtarget.com/rms/onlineimages/networking-compare_cellular_vs_millimeter_wave-f.png 1280w" alt="An illustration of wavelength and frequency differences between cellular and mmWave. " height="260" width="559"> <figcaption> <i class="icon pictures" data-icon="z"></i>Millimeter wave speeds are between 30 GHz and 300 GHz. </figcaption> <div class="main-article-image-enlarge"> <i class="icon" data-icon="w"></i> </div> </figure> </section> <section class="section main-article-chapter" data-menu-title="What are the benefits of 5G?"> <h2 class="section-title"><i class="icon" data-icon="1"></i>What are the benefits of 5G?</h2> <p>5G offers compelling benefits over older networks, including the following:</p> <ul class="default-list"> <li>Supports more applications using higher frequencies and higher bandwidth.</li> <li>Provides enhanced mobile broadband coverage and connectivity.</li> <li>Offers significantly lower latency and faster speeds for uploads and downloads.</li> <li>Supports new technology options such as 4K streaming or near-real-time streaming of virtual reality (VR).</li> <li>Provides more accurate data transmissions due to lower block error rates.</li> </ul> <p>Since 5G operates on a wider bandwidth range, it offers higher capacity and throughput. The expanded bandwidth range enables more devices to connect to a single 5G network and send and receive data simultaneously without appreciable degradation in data transmission speed or accuracy. The fast speeds and lower latency of 5G mean it can handle the more rigorous connectivity and data requirements of new technologies and devices.</p> </section> <section class="section main-article-chapter" data-menu-title="What are the drawbacks of 5G?"> <h2 class="section-title"><i class="icon" data-icon="1"></i>What are the drawbacks of 5G?</h2> <p>A downside of 5G is its limited coverage and range. <a href="https://www.computerweekly.com/news/366632895/UK-networks-commit-to-pay-39m-to-secure-mmWave-5G-spectrum">Higher-frequency mmWaves</a> can be easily blocked, so reliable operation depends on direct line-of-sight connections. This problem can significantly decrease signal strength and cause communication interruptions. Providers can mitigate this with directional antennas and dense base station networks.</p> <p>5G networks can also be jammed in the mmWave frequency band. Malicious actors can use high-gain directional antennae to aim powerful jamming signals that prevent the intended receiver from receiving the transmitted signal. Some cyber attackers also use opportunistic wiretapping and jamming to cause severe network degradation and service interruptions based on specific conditions.</p> <p>The development of <a href="https://www.computerweekly.com/feature/Are-AI-agents-a-blessing-or-a-curse-for-cyber-security">AI-based attack tools</a> also enables sophisticated threat actors to execute high-volume, advanced swarm attacks against 5G networks and devices. A few sophisticated attackers also use IoT and IIoT networks and application programming interfaces to manipulate 5G networks, execute distributed denial-of-service and ransomware attacks, and evade detection by traditional security tools.</p> <p><a href="https://www.techtarget.com/searchcloudcomputing/tip/The-pros-and-cons-of-sovereign-clouds">Privacy concerns</a> are another issue. 5G networks use cloud-based data storage. However, operators cannot always protect user data stored in the cloud. Many might not even try to if they operate in countries with less stringent data privacy regulations. This can seriously endanger user privacy and lead to issues like identity theft, harassment or extortion.</p> <p>Threat actors can potentially use user location information – discoverable on 5G networks -- in malicious ways to target or harm specific users. They can <a href="https://www.computerweekly.com/news/252485535/Police-secrecy-over-IMSI-catcher-mass-surveillance-of-mobile-phones">seize the International Mobile Subscriber Identity</a> of a subscriber's device to monitor or eavesdrop on that person’s call activity.</p> <p>Deploying 5G requires significant technical and financial resources. In some countries, operators may not have access to these resources, so their users cannot fully benefit from 5G connectivity in terms of speed, latency and reliability. Even in countries where 5G is becoming the norm, there can be an <a href="https://www.computerweekly.com/news/366627549/Urban-rural-connectivity-gap-widens-in-OECD-countries">implementation divide between urban and rural areas.</a> Urban areas tend to have higher internet and mobile penetration, resulting in faster 5G deployment compared to rural areas. Consequently, rural users might not benefit from 5G at the same pace as their urban counterparts.</p> </section> <section class="section main-article-chapter" data-menu-title="The launch of 5G"> <h2 class="section-title"><i class="icon" data-icon="1"></i>The launch of 5G</h2> <p>Cellular companies in South Korea began deploying 5G networks in 2019 as the successor to 4G, making the Asian country the first to offer 5G to its cellphone users. Around the same time, the first 5G-compliant smartphones and associated devices began to become commercially available.</p> <p>Initially, carrier 5G deployments were underwhelming, as some companies opted to expand their low-band infrastructure first. Although still 5G, it was not providing the blinding speed many carriers advertised -- as that would come with the emergence of mmWave spectrums. In the U.S., Verizon was a market leader in building its 5G mmWave architecture, rolling out its 5G network in 2019.</p> <p>Since 2019, many carriers in the U.S. and elsewhere have expanded their 5G Sub-6 and mmWave deployments. After Verizon, Sprint, AT&T and T-Mobile started rolling out expansive 5G networks. Today, many carriers offer coverage maps on their websites, showing where they provide 5G mmWave, Sub-6 or 4G coverage. Most carriers offer different plans for each band, with varying price points. For example, Verizon's fastest 5G plan, Unlimited Ultimate, offers 5G Ultra Wideband with enhanced video calling and streaming capabilities. The next fastest plan is also for 5G Ultra Wideband, albeit with fewer features than the fastest plan. Both plans are four times faster than the regular 5G plan.</p> </section> <section class="section main-article-chapter" data-menu-title="What types of 5G wireless services are available?"> <h2 class="section-title"><i class="icon" data-icon="1"></i>What types of 5G wireless services are available?</h2> <p>Network operators offer the following types of 5G services:</p> <ol class="default-list"> <li><a href="https://www.techtarget.com/searchnetworking/tip/Top-5G-use-cases-for-business-include-fixed-wireless-healthcare">5G cellular services</a> provide user access to operators' 5G cellular networks. The first services were rolled out in 2019. Cellular service delivery is also dependent upon the completion of mobile core standards by the 3<sup>rd</sup> Generation Partnership Project (<a href="https://www.techtarget.com/searchnetworking/definition/3rd-Generation-Partnership-Project-3GPP">3GPP)</a>.</li> <li><a href="https://www.techtarget.com/searchnetworking/definition/private-5G">Private 5G</a> delivers 5G cellular connectivity for private network use cases. An organization must own or rent 5G spectrum and infrastructure to enact a private 5G network. Private 5G networks function similarly to public 5G networks, but owners can provide restricted access to their own network. Private 5G networks can be deployed as either a service, wholly owned, hybrid or sliced private networks.</li> <li>5G <a href="https://www.techtarget.com/searchmobilecomputing/definition/fixed-wireless">fixed wireless</a> broadband services deliver internet access to homes and businesses without a wired connection to the premises. To achieve this, network operators deploy New Radio in small cell sites near buildings to beam a signal to a receiver on a rooftop or windowsill, which is then amplified within the premises. <a href="https://www.computerweekly.com/news/365534004/Broadband-services-to-drive-Australia-and-India-fixed-communications">Fixed broadband services</a> lower operator costs by eliminating the need to roll out fiber optic lines to every residence. Instead, operators need only install fiber optics to cell sites, and customers receive broadband services through wireless modems in their residences or businesses.</li> </ol> <p>In the U.S., all major telecom providers provide 5G wireless broadband services for consumer and business use. Users can select from multiple plans, tailored to their specific connectivity requirements and budget. Higher-speed plans with more reliable coverage, router upgrades and other features cost more than lower-speed plans. But even with a lower-speed plan, 5G services are usually faster and more reliable than 4G and older networks.</p> </section> <section class="section main-article-chapter" data-menu-title="5G vs. 4G: Key differences"> <h2 class="section-title"><i class="icon" data-icon="1"></i>5G vs. 4G: Key differences</h2> <p>Each generation of cellular technology differs in its data transmission speed and encoding methods, which require end users to upgrade their hardware. 4G can support up to 2 Gbps -- although peak speeds can also go down to 1 Gbps -- and is continuing to improve in speed. 4G offers speeds up to 500 times faster than 3G. 5G can be up to 100 times faster than 4G.</p> <p>Latency is a key differentiator between 4G and 5G, with 5G offering superior performance. 5G uses OFDMA encoding, like 4G LTE. 4G, however, uses 20 MHz channels bonded together at 160 MHz. 5G uses a wider range of frequencies and can have channels between 100 and 800 MHz, which require larger blocks of airwaves than 4G.</p> <p>The bandwidth range also distinguishes 5G from predecessor networks. Unlike older networks that operated in the Sub-3 GHz range, 5G expands its radio spectrum resources to 100 GHz and greater.</p> <p>Another difference between 5G and 4G is smaller transmitters. With 5G, these devices consume less power, and more transmitters can be placed in various locations – such as the top of a building – to divide a service area into smaller cells. These cells act as base stations, connecting users within those cells to the 5G network. In contrast, 4G uses larger cells that require more power but still underperform 5G.</p> <p>Network Block Error Rate (BER) is another area where 5G shines. 5G BER, a measure of data transmission quality, is very low -- near zero -- compared to 3G and 4G. That's because 5G uses adaptive Modulation and Coding Scheme (MCS) in which the transmitter automatically lowers the transmission speed when the error rate increases to a specific level. Very high real-time transmission accuracy is secured in exchange for a small drop in transmission speed.<b> </b></p> <div class="youtube-iframe-container"> <iframe id="ytplayer-0" src="https://www.youtube.com/embed/NZtMrEPjpQ4?autoplay=0&modestbranding=1&rel=0&widget_referrer=null&enablejsapi=1&origin=https://www.techtarget.com" type="text/html" height="360" width="640" frameborder="0" loading="lazy"></iframe> </div> </section> <section class="section main-article-chapter" data-menu-title="Is 5G a replacement for 4G?"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Is 5G a replacement for 4G?</h2> <p>The answer is: <i>not yet</i>. Although 5G service is now widely available almost everywhere, it's not a full replacement for 4G as many expected. While there are areas today with fast multi-gigabit download speeds, most users will still encounter mid- or low-band 5G speeds. Even in a city block that provides mmWave 5G, frequencies can be blocked by obstacles, which means 5G speed will diminish if the signal must travel through, say, a wall. Because of this, users might notice only a minor speed improvement compared to 4G. 5G speeds are still considered fast in most cases, facilitating use cases such as wirelessly streaming videos in 4K resolutions.</p> </section> <section class="section main-article-chapter" data-menu-title="5G use cases"> <h2 class="section-title"><i class="icon" data-icon="1"></i><a href="https://www.idtechex.com/en/research-article/why-do-we-need-6g-and-what-are-the-challenges/28805"></a>5G use cases</h2> <p>5G supports a wide range of use cases, ranging from business and enterprise use to more casual consumer use. Some examples include:</p> <ul class="default-list"> <li>Streaming high-quality video.</li> <li>Seamless, low-cost, highly scalable communication among devices in an IoT environment.</li> <li>More accurate location tracking.</li> <li>Fixed wireless services.</li> <li>Low-latency mobile communication.</li> <li>Improved real-time business analytics.</li> <li>Immersive experiences with VR and augmented reality.</li> <li>Reliable and real-time remote control of critical infrastructure.</li> <li>Real-time information-sharing among healthcare professionals.</li> <li>Real-time patient monitoring through IoT-connected devices.</li> <li>Seamless connectivity between devices for traffic management, environmental management and city planning.</li> <li>Monitoring of carbon emissions and other pollutants aligned to <a href="https://www.techtarget.com/sustainability/feature/ESG-strategy-and-management-Complete-guide-for-businesses">environmental, social and governance</a> and sustainability goals.</li> <li>Creation of industrial ecosystems with reliable closed-loop process automation and predictive maintenance.</li> </ul> <p>In addition to improvements in speed, capacity and latency, 5G offers network management features such as <a href="https://www.techtarget.com/whatis/definition/network-slicing">network slicing</a>, which enables mobile operators to create multiple virtual networks in a single 5G network. This enables wireless network connections to support specific uses or business cases and could be sold on an as-a-service basis. A self-driving car, for example, could require a network slice that offers extremely fast, low-latency connections so a vehicle could navigate in real time. A home appliance could be connected using a lower-power, slower connection because high performance is not crucial. IoT could use secure, data-only connections.</p> </section> <section class="section main-article-chapter" data-menu-title="Business benefits of 5G"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Business benefits of 5G</h2> <p>5G's value chain and its support of a broad range of industries have led to a notable effect on the global tech and business landscape and on national economies. By the end of 2025, global 5G population coverage is expected to reach 60%, according to a <a target="_blank" href="https://www.ericsson.com/en/reports-and-papers/mobility-report/dataforecasts/network-coverage#:~:text=The%20build%2Dout%20of%205G,around%2085%20percent%20in%202029." rel="noopener">report by Ericsson</a>. By 2031, global 5G coverage -- outside Mainland China -- is expected to increase to 85%. In North America, both the popularity and coverage of 5G are increasing. At the end of 2024, service providers had deployed 5G across low-, mid- and high-band frequencies. While mid-band coverage reached 90%, total coverage reached 95%, showing that 5G coverage is increasing rapidly and could eventually eclipse 4G coverage.</p> <p>A <a target="_blank" href="https://www.pwc.com/gx/en/industries/technology/publications/economic-impact-5g.html" rel="noopener">PwC study</a> forecasts that 5G will contribute $484 billion to the U.S. economy by 2030. In industrial manufacturing alone, 5G is expected to add $15 billion to the U.S. economy by 2030. On a global scale, the report predicts that the total effect of 5G on global GDP will reach $1.3 trillion. According to PwC, the five areas where 5G will have the most influence include the following:</p> <ul class="default-list"> <li>Healthcare: $530 billion</li> <li>Smart utilities: $330 billion</li> <li>Consumer and media applications: $254 billion</li> <li>Industrial manufacturing: $134 billion</li> <li>Financial services: $85 billion</li> </ul> </section> <section class="section main-article-chapter" data-menu-title="Who is working on 5G?"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Who is working on 5G?</h2> <p>Many of the major carriers, including AT&T, T-Mobile, and Verizon, are working to expand their 5G networks. These carriers generally support a multi-tier 5G strategy that encompasses low-band, mid-band, and mmWave frequencies.</p> <p>The 3GPP is updating its 5G specifications. In June 2025, it released 5G Advanced Release 20 (Rel-20 5G-Advanced). This is the sixth technology standard release for 5G Advanced. It includes numerous enhancements to 5G use cases and deployments, laying the foundation for the <a href="https://www.computerweekly.com/news/366624934/Sweden-claims-worlds-first-6G-edge-connected-vehicle-test-facility">future 6G</a> wireless standard.</p> </section> <section class="section main-article-chapter" data-menu-title="Why 5GE is not really 5G"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Why 5GE is not really 5G</h2> <p>Early in its 5G development, AT&T introduced a 5G Evolution network, where 4G LTE users received an update that purportedly <i>upgraded</i> them to 5GE. 5GE was just a rebranding of AT&T's Gb 4G LTE network, however.<a name="_Hlk208848137"></a> In this sense, it is not <i>true</i> 5G.</p> <p>AT&T argued that the speeds offered with 5GE were sufficiently close to those of 5G. <a name="_Hlk208848148"></a>Even so, it still was not technically 5G. It does not align with the 5G cellular standard defined by the 3GPP and does not offer the same high speeds and low latency as 5G. The <i>G </i>in these terms typically stands for generation, indicating a compatibility break with previous hardware. Simply put, 5GE is an iteration of and an <i>improvement</i> over 4G LTE, rather than an <i>upgrade</i> to 5G. Users would not have been able to update their phones to support 5G; rather, they would have needed to get a new phone that supports 5G. This was a marketing strategy that misled individuals who did not know the specifics behind the technology.</p> </section> <section class="section main-article-chapter" data-menu-title="What 5G phones are available?"> <h2 class="section-title"><i class="icon" data-icon="1"></i>What 5G phones are available?</h2> <p>A phone or another piece of hardware cannot simply receive a software update on a 4G phone to enable 5G. 5G requires specific hardware. To use 5G, a user must have a device that supports 5G, a carrier that supports 5G, and be within range of a 5G node. Additionally, the mobile provider should offer 5G plans, and users must sign up for a suitable plan.</p> <p>Most new phones support 5G, and all major cellphone manufacturers now offer 5G-enabled phones. Yet devices are available that are not 5G-enabled. They are older models or budget phones that lack the necessary hardware, including 5G modems to connect to 5G networks.</p> </section> <section class="section main-article-chapter" data-menu-title="5G vs. 6G"> <h2 class="section-title"><i class="icon" data-icon="1"></i>5G vs. 6G</h2> <p>The sixth generation of cellular technology, or 6G, is expected to provide even faster speeds, even lower latency -- to the tune of microseconds -- and even better connectivity than 5G. Additionally, 6G is likely to operate at higher radio frequencies, enabling it to carry more data and provide greater bandwidth than 5G.</p> <p><a href="https://www.computerweekly.com/news/366621254/Ericsson-SoftBank-team-to-seek-out-6G-XR-AI-potential">6G is also expected to have built-in AI</a> and ML capabilities. This will expand 5G's existing wireless communication infrastructure and support even more high-end applications where issues like buffering and lag are unacceptable. Some experts also predict that 6G will help scale up machine-to-machine communication, such as the communication that occurs within IoT and IIoT networks.</p> <p>As of 2025, research and development into 6G is progressing at a steady pace, with telecom providers, device manufacturers, universities and governments all working to develop technologies and hardware that can support 6G networks. However, 6G is not yet publicly available. Some <a target="_blank" href="https://www.idtechex.com/en/research-article/why-do-we-need-6g-and-what-are-the-challenges/28805" rel="noopener">researchers</a> and industry watchers predict deployment between 2028 and 2030.</p> </section> <section class="section main-article-chapter" data-menu-title="History of cellular wireless technology"> <h2 class="section-title"><i class="icon" data-icon="1"></i>History of cellular wireless technology</h2> <p>Nippon Telegraph and Telephone launched 1G in 1979. By 1984, Japan became the first country to have a nationwide generational network. Motorola introduced the first commercially available cellphone in 1983, called the DynaTAC.</p> <p>The second generational network, 2G, emerged in Finland in 1991. It provided significant improvements to mobile talk, such as enhanced sound quality and reduced static, and introduced encrypted calls. Another major 2G addition was the ability to access media on cell phones by enabling the transfer of data bits.</p> <p>3G wireless debuted in 2001. It focused on standardizing network protocols from different vendors. The biggest improvement was its increased speed, which enabled users to browse the internet on their mobile devices. 3G had four times the data transferring capability compared to 2G. International roaming services were introduced.</p> <p>4G surfaced in 2009. Users could stream high-quality video with faster mobile web access. In 2011, LTE networks began launching in Canada. 4G LTE remains common in areas where 5G is not yet available.</p> <p>The 3GPP began its work on 5G in 2015. Its focus was to develop globally applicable specifications for 3G mobile systems. The 3GPP meets four times annually to plan and develop new releases. Each release builds upon the previous one, providing new, standardized functionalities.</p> <p>In 2017, the fifth 5G and 5G NR specifications were released. It was a new radio access technology developed by the 3GPP for use on 5G mobile networks. In 2018, the 3GPP approved Release 16, which included several specifications, including network slicing.</p> <p>In 2019, Verizon was among the first carriers to develop a 5G mobile network in two U.S cities: Chicago and Minneapolis. Other carriers in the U.S., such as Sprint, AT&T, and T-Mobile, began launching their own 5G infrastructure and services around the same time. Some companies started focusing on higher-speed mmWave infrastructure, while others decided to invest in developing lower-band frequencies first.</p> <p>In 2020, 3GPP Release 16 was published, covering applications of 5G such as automotive and IIoT. Release 18, launched in 2022, covered system architecture and services, security, multimedia codecs, management orchestration and charging features.</p> <p>In 2025, 3GPP released 5G Advanced Release 20, designed to enhance the current capabilities of 5G with critical upgrades to service requirements, system architecture and protocol details. All service requirements were frozen in June 2025. 3GPP expects to complete 80% of the system architecture aspects of Rel-20 5G-Advanced by June 2026, with all aspects to be frozen by September. The 5G protocol details are planned for completion in March 2027, with the final ASN.1/OpenAPI freeze planned for June 2027.</p> <p><i>As 5G adoption evolves, we will see new iterations, updates and improvements. Learn more about </i><a href="https://www.techtarget.com/whatis/feature/5-Predictions-about-5G-Adoption-in-2021-and-Beyond"><i>5G adoption</i></a><i> and how different industries will benefit from it.</i></p> </section> Fifth-generation wireless or 5G is a global standard and technology for wireless and telecommunications networks. https://cdn.ttgtmedia.com/visuals/digdeeper/2.jpg https://www.techtarget.com/searchnetworking/definition/5G Fri, 05 Dec 2025 14:15:00 GMT What is 5G? <p>6G (sixth-generation wireless) is the successor to <a href="https://www.techtarget.com/searchnetworking/definition/5G">5G</a> cellular technology and is expected to be globally available by around 2030. <a href="https://www.computerweekly.com/feature/6G-networks-explained-everything-you-need-to-know">6G networks</a> will be able to use higher <a href="https://www.techtarget.com/searchnetworking/definition/radio-frequency">frequencies</a> than 5G networks and provide substantially higher capacity and much lower latency. One of the goals of the 6G internet is to support communications with one-microsecond latency. This is 1,000 times faster -- or 1/1000th the latency -- than one millisecond <a href="https://www.techtarget.com/searchnetworking/definition/throughput">throughput</a>.</p> <p>The 6G technology market is expected to facilitate significant improvements in areas such as imaging, presence technology and location awareness. Working in conjunction with technologies like AI, the 6G computational infrastructure will be able to automatically identify the optimal location for computing to occur, including decisions about data storage, processing and sharing. In this way, it has the potential to deliver extraordinary performance and create new possibilities across a <a target="_blank" href="https://www.lightreading.com/6g/what-at-t-really-wants-from-6g" rel="noopener">wide range of applications</a> and industries.</p> <p>6G will be based on 3rd Generation Partnership Project (3GPP) standards. 3GPP is the same organization that creates and maintains the 5G and <a href="https://www.techtarget.com/whatis/definition/5G-New-Radio-NR">5G New Radio</a> (NR) standards for wireless communications. It is important to note that 6G is not yet a fully functioning technology. Although governments and the private sector are investing substantial effort and financial resources in researching and developing this next-generation wireless standard, industry specifications for 6G-enabled network products remain years away. Some telecommunications companies, such as Ericsson, expect that the earliest 6G will be available for commercial markets is in the early 2030s.</p> <section class="section main-article-chapter" data-menu-title="What are the advantages of 6G vs. 5G?"> <h2 class="section-title"><i class="icon" data-icon="1"></i>What are the advantages of 6G vs. 5G?</h2> <p>Like 5G, 6G is expected to use multiple <a href="https://www.techtarget.com/searchnetworking/definition/band">frequency bands</a> for wireless communications. Mainly, though, 6G networks will operate by using signals at the higher end of the radio spectrum. As of 2025, it is still too early to approximate 6G data rates.</p> <p>In 2021, LG demonstrated its ability to transmit and receive 6G data over 100 meters outdoors; during the same trial, LG also successfully demonstrated adaptive <a href="https://www.techtarget.com/searchnetworking/definition/beamforming">beamforming</a>. In 2022, researcher Mahyar Shirvanimoghaddam, associate professor at The University of Sydney, suggested that a theoretical peak data rate of 1 terabit per second (Tbps) might be possible for wireless data transfers on 6G. That estimate applies to data transmitted in short bursts across limited distances.</p> <p>In September 2025, scientists in the U.S. and China developed a small, full-spectrum 6G chip capable of transferring data at 100 gigabits per second (Gbps). Considering that the top-performing 5G networks in the U.S. offered <a target="_blank" href="https://www.ookla.com/research/reports/united-states-speedtest-connectivity-report-h1-2025" rel="noopener">5G download speeds</a> of around 300 megabits per second (Mbps), the possibility of 6G reaching 100 Gbps would make it around 10,000 times faster than 5G.</p> <p>One way to understand these differences is with a real-world example.</p> <p>Consider a high-definition movie file that is 3 GB. If downloading the movie over a 3G network takes two hours, it will take about 20 minutes over a 4G network. A <a href="https://www.techtarget.com/searchnetworking/feature/Understand-the-basics-of-5G-wireless-networks">5G network</a> further speeds up downloads, with only two minutes needed to download the entire movie. Even so, 5G speeds are still a lot less than what might be possible with 6G. If a speed of 1 Tbps is achieved, downloading the movie could take a fraction of a second over a 6G network.</p> <p>The ultra-high levels of capacity and ultra-low latency offered by 6G will help to advance the technologies introduced in 5G and extend the performance of 5G applications. It will also expand the scope of capabilities to support new and innovative applications in wireless connectivity, cognition, sensing, imaging, <a href="https://www.techtarget.com/searcherp/definition/digital-twin">digital twinning</a>, autonomous vehicles and mixed reality. With 6G, access points will be able to serve multiple clients simultaneously using <a href="https://www.techtarget.com/searchnetworking/definition/orthogonal-frequency-division-multiple-access-OFDMA">orthogonal frequency-division multiple access</a>.</p> <figure class="main-article-image full-col" data-img-fullsize="https://www.techtarget.com/rms/onlineImages/telecom_5G_features.jpg"> <img data-src="https://www.techtarget.com/rms/onlineImages/telecom_5G_features_mobile.jpg" class="lazy" data-srcset="https://www.techtarget.com/rms/onlineImages/telecom_5G_features_mobile.jpg 960w,https://www.techtarget.com/rms/onlineImages/telecom_5G_features.jpg 1280w" alt="An illustration of a smartphone displaying " height="258" width="560"> <figcaption> <i class="icon pictures" data-icon="z"></i>6G is expected to significantly enhance many of the key features of 5G networks. </figcaption> <div class="main-article-image-enlarge"> <i class="icon" data-icon="w"></i> </div> </figure> <p>6G's higher frequencies will enable much faster sampling rates than with 5G. They will also provide significantly better throughput and higher data rates. The use of sub-millimeter waves -- wavelengths less than <a href="https://www.techtarget.com/searchnetworking/definition/millimeter-wave-MM-wave">1 millimeter</a> -- and frequency selectivity to determine relative electromagnetic absorption rates is expected to advance the development of <a href="https://www.computerweekly.com/news/366622918/ETSI-highlights-integrated-sensing-communication-6G-use-cases">wireless sensing technology</a>.</p> <p>Mobile <a href="https://www.techtarget.com/searchdatacenter/definition/edge-computing">edge computing</a> will be built into all 6G networks, whereas it must be added to existing 5G networks. Edge and core computing will be more integrated as part of a combined communications and computation infrastructure framework by the time 6G networks are deployed. This approach will provide many potential advantages as 6G technology becomes operational. These benefits include improved access to AI capabilities, support for sophisticated mobile devices and systems, and additional value creation in many industries due to increased service differentiation and support for more enterprise applications and use cases. Additionally, <a href="https://www.computerweekly.com/news/366624934/Sweden-claims-worlds-first-6G-edge-connected-vehicle-test-facility">6G and edge computing</a> will facilitate more seamless connections between people, devices and the internet, redefining the meaning and application of wireless communications in the future.</p> <div class="youtube-iframe-container"> <iframe id="ytplayer-0" src="https://www.youtube.com/embed/5HlmWddw6_0?autoplay=0&modestbranding=1&rel=0&widget_referrer=null&enablejsapi=1&origin=https://www.techtarget.com" type="text/html" height="360" width="640" frameborder="0" loading="lazy"></iframe> </div> </section> <section class="section main-article-chapter" data-menu-title="When will 6G internet be available?"> <h2 class="section-title"><i class="icon" data-icon="1"></i>When will 6G internet be available?</h2> <p>6G internet is expected to launch commercially around 2030. In March 2024, the 3GPP published a timeline for 6G development and deployment. According to this timeline, 6G technical performance requirements are expected to be defined by 2026. The actual specifications will be included in Release 21 by 2028. Each release reflects the 3GPP's ongoing development work for 5G and 6G. Work on Release 20, which contains dual-track frameworks for 5G-Advanced and early 6G, began in early 2025.</p> <p>While some early discussions have taken place to define the technology, 6G research and development (R&D) activities started in earnest in 2020. A year earlier, in 2019, the U.S. Federal Communications Commission (FCC) opened the frequency spectrum between 95 GHz and 3,000 GHz. This has contributed to the accelerated development of new wireless communication technologies, including 6G, for wide use in the U.S.</p> <p>Furthermore, new use cases for <a href="https://www.techtarget.com/whatis/definition/5G-New-Radio-NR">5G New Radio</a> systems operating at bands beyond 52.6 GHz are emerging. This is likely to result in future wireless systems using the terahertz (THz) band, which has a lot of available bandwidth. The THz band could provide the means for achieving the Tbps-level data rates of 6G.</p> </section> <section class="section main-article-chapter" data-menu-title="How will 6G work?"> <h2 class="section-title"><i class="icon" data-icon="1"></i>How will 6G work?</h2> <p>The exact working of 6G technology is not yet known. However, it is expected to make greater use of the distributed radio access network (<a href="https://www.techtarget.com/searchnetworking/definition/radio-access-network-RAN">RAN</a>) and the THz spectrum to increase capacity, lower latency and improve spectrum sharing. It will selectively use different frequencies and adjust wavelengths to deliver high data transfer speeds and support a wide range of applications.</p> <p>6G will also use sophisticated methods to improve <a href="https://www.techtarget.com/searchmobilecomputing/definition/spectrum-efficiency">spectral efficiency</a> and facilitate seamless duplex communications. Additionally, 6G networks are likely to be based on a mesh networking paradigm, which will help extend network coverage.</p> <p>6G will have significant implications for many government and industry approaches to public safety and critical asset protection, such as the following areas:</p> <ul class="default-list"> <li>Threat detection.</li> <li><a href="https://www.techtarget.com/searchnetworking/feature/5G-in-healthcare-9-benefits-and-use-cases">Health monitoring</a>.</li> <li>Feature and <a href="https://www.techtarget.com/searchenterpriseai/definition/facial-recognition">facial recognition</a>.</li> <li>Decision-making in areas like law enforcement and social credit systems.</li> <li>Air-quality measurements.</li> <li>Gas and toxicity sensing.</li> <li>Sensory interfaces.</li> </ul> <p>Improvements in these areas will also benefit smartphone and other mobile network technology, as well as emerging technologies, such as smart cities, autonomous vehicles, virtual reality (VR) and truly <a href="https://www.techtarget.com/searchnetworking/tip/Top-use-cases-for-5G-augmented-and-virtual-reality">immersive augmented reality</a> (AR).</p> <figure class="main-article-image half-col" data-img-fullsize="https://www.techtarget.com/rms/onlineimages/whatis-6G_characteristics-h.png "> <img data-src="https://www.techtarget.com/rms/onlineimages/whatis-6G_characteristics-h_half_column_mobile.png " class="lazy" data-srcset="https://www.techtarget.com/rms/onlineimages/whatis-6G_characteristics-h_half_column_mobile.png 960w,https://www.techtarget.com/rms/onlineimages/whatis-6G_characteristics-h.png 1280w" alt="An infographic about 6G technology, featuring bullet points listing key features such as terabit speed, AI core networking and more. " height="440" width="279"> <figcaption> <i class="icon pictures" data-icon="z"></i>6G will introduce capabilities such as terahertz signal transmission. </figcaption> <div class="main-article-image-enlarge"> <i class="icon" data-icon="w"></i> </div> </figure> </section> <section class="section main-article-chapter" data-menu-title="Do we even need 6G?"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Do we even need 6G?</h2> <p>There are several reasons 6G technology is needed:</p> <ul class="default-list"> <li><b>Technology convergence.</b> The sixth generation of cellular networks will integrate previously disparate technologies, such as deep learning and <a href="https://www.techtarget.com/searchbusinessanalytics/definition/big-data-analytics">big data analytics</a>. The introduction of 5G has paved the way for much of this convergence, which 6G will further support and simplify.</li> <li><b>Edge computing. </b>The need to deploy edge computing to ensure overall throughput and low latency for ultra-reliable, low-latency communications solutions is a key driver of 6G.</li> <li><b>Internet of things.</b> Another driving force is the need to support machine-to-machine (<a href="https://www.techtarget.com/iotagenda/definition/machine-to-machine-M2M">M2M</a>) communication in <a href="https://www.techtarget.com/iotagenda/definition/Internet-of-Things-IoT">IoT</a>.</li> <li><b>High-performance computing.</b> There is a strong relationship between 6G and <a href="https://www.techtarget.com/searchdatacenter/definition/high-performance-computing-HPC">HPC</a>. While edge computing resources will handle some of the IoT and mobile technology data, much of it will require more centralized HPC resources for processing.</li> </ul> </section> <section class="section main-article-chapter" data-menu-title="Who is working on 6G technology?"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Who is working on 6G technology?</h2> <p>Many countries and industry players are competing in the race to deploy 6G. Within the industry, test and measurement vendor Keysight Technologies has committed to its development, while major telecom infrastructure companies -- including Huawei, Nokia and Samsung -- have signaled that they are investing substantial resources into <a target="_blank" href="https://www.lightreading.com/6g/6g-is-forking-with-consequences-for-ericsson-huawei-and-nokia" rel="noopener">6G R&D</a>.</p> <p>The major 6G projects underway worldwide include the following:</p> <ul class="default-list"> <li><b>The University of Oulu in Finland</b> launched the 6Genesis research <a target="_blank" href="https://www.oulu.fi/6gflagship/" rel="noopener">project to develop a 6G vision</a> for 2030. The university has also signed a collaboration agreement with Japan's Beyond 5G Promotion Consortium to coordinate the work of the Finnish 6G Flagship research on 6G technologies.</li> <li><b>South Korea's Electronics and Telecommunications Research Institute</b> is conducting research on the THz frequency band for 6G. It envisions data speeds 100 times faster than 4G Long-Term Evolution (<a href="https://www.techtarget.com/searchmobilecomputing/definition/Long-Term-Evolution-LTE">LTE</a>) networks and five times faster than 5G networks. Additionally, in 2023, the country's Science Ministry unveiled its $324.5 million R&D plan for developing 6G technologies and standards.</li> <li><b>China's Ministry of Industry and Information Technology</b> is investing in and monitoring 6G R&D in the country.</li> <li><b>The U.S. FCC </b>in 2020 opened up 6G frequency for spectrum testing for frequencies over 95 GHz to 3 THz.</li> <li><b>Major U.S. cellular service providers</b> such as AT&T, Verizon and T-Mobile, along with tech giants such as Apple, Google, HP Enterprise and Intel have created the <a target="_blank" href="https://www.lightreading.com/6g/next-g-alliance-offers-holistic-view-of-6g-in-north-america" rel="noopener">Next G Alliance</a>, a private-sector initiative to develop and commercialize 6G technology in North America and advance North American leadership in 6G innovation and realization.</li> <li><b>Hexa-X</b> is a European consortium of academic and industry leaders working to lay the technical foundation for the 6G era. It aims to promote openness and collaboration among researchers, standardization bodies and policymakers, and works on developing an open, modular and flexible framework to mitigate known 6G research challenges.</li> <li><b>Hexa-X-II </b>is the 6G flagship project of the European Smart Networks and Services Joint Undertaking. Where Hexa-X laid the foundation for 6G by clarifying 6G vision, defining basic concepts and describing key technology enablers, Hexa-X-II focuses on research into end-to-end system design that will be needed to deliver novel services on 6G networks. Hexa-X-II also aims to design a system blueprint for an inclusive and trustworthy 6G platform, addressing implementation aspects by defining various use cases, services and requirements.</li> <li><b>Osaka University in Japan and Australia's Adelaide University</b> researchers have developed a silicon-based microchip with a special <a href="https://www.techtarget.com/searchnetworking/definition/multiplexing">multiplex</a> to divide data and enable more efficient management of terahertz waves. During testing, researchers claimed the device transmitted data at 11 Gbps compared to 5G's theoretical limit of 10 Gbps of 5G.</li> </ul> </section> <section class="section main-article-chapter" data-menu-title="Recent developments in 6G"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Recent developments in 6G</h2> <p>In December 2023, the International Telecommunications Union published its 6G framework, <a target="_blank" href="https://www.itu.int/en/mediacentre/Pages/PR-2023-12-01-IMT-2030-for-6G-mobile-technologies.aspx" rel="noopener">IMT-2030</a>. This framework highlights the new capabilities that will be enabled by 6G, new usage scenarios based on current and future technology trends, and the potential impact of 6G on various industries.</p> <p>In December 2024, the 3GPP, following recommendations from certain companies in the telecom industry, decided that a channel bandwidth of 200 MHz should be considered for 6G. It also recommended a carrier frequency of 7 GHz for the use of 200 MHz channel bandwidths for 6G. Of course, the availability of this bandwidth remains a challenge, as higher bandwidths are typically used for non-commercial purposes, such as defense, raising the issue of how to make it available to enable the <i>democratization</i> of 6G.</p> <p>Private companies are particularly keen on developing and commercializing 6G as soon as possible. One example is South Korea-headquartered Samsung. In July 2020, Samsung released a <a target="_blank" href="https://news.samsung.com/global/samsungs-6g-white-paper-lays-out-the-companys-vision-for-the-next-generation-of-communications-technology" rel="noopener">white paper</a> titled <i>6G: The Next Hyper-Connected Experience for All </i>outlining the company’s vision for 6G and its initial expectation of the 6G timeline. Samsung expects the earliest commercialization of 6G to occur as soon as 2028, followed by massive commercialization around 2030. The white paper also describes other important issues in 6G development:</p> <ul class="default-list"> <li>Megatrends like connected machines and openness of mobile communications.</li> <li>The chief requirements to realize the expected 6G services, including high data rates, air latency less than 100 microseconds, higher network coverage and higher device connection density.</li> <li>The technologies that will be essential to satisfy these requirements, including multiple input, multiple output (<a href="https://www.techtarget.com/searchmobilecomputing/definition/MIMO">MIMO</a>), metamaterial antennae, split computing and more flexible <a href="https://www.techtarget.com/searchnetworking/definition/network-topology">network topologies</a>.</li> </ul> <p>In 2024, China launched a 6G test satellite equipped with a THz system into <a href="https://www.techtarget.com/searchnetworking/tip/A-look-at-low-Earth-orbit-use-cases">low Earth orbit</a>. This was the world's first 6G satellite, and it uses high-frequency THz waves. The satellite, which will orbit at an altitude of around 310 miles, offers much higher data transfer rates and lower latency than higher-orbit satellites -- creating the possibility of delivering high-speed internet to remote areas. According to a 2023 white paper from the International Telecommunication Union, China aims to commercialize 6G technologies by 2030.</p> <p>The U.S is also scaling up R&D into 6G development and deployment. In February 2024, the White House issued a joint statement with nine other governments to help guide international research into 6G. The statement envisions that 6G will be secure, open and resilient by design. The National Telecommunications and Information Administration (NTIA) supports the development of 6G for U.S. consumers and innovators. It also works with other federal agencies -- including the FCC and the Commerce Spectrum Management Advisory Committee -- to advance the country's 2023 National Spectrum Strategy and ensure U.S. leadership in the development of global 6G standards. The NTIA also promotes openness, interoperability, security and reliability of future 6G deployments.</p> </section> <section class="section main-article-chapter" data-menu-title="Future scope of 6G networks"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Future scope of 6G networks</h2> <p>In the early 2010s, the phrase <i>Beyond 4G</i> (B4G) was coined to refer to the need to advance the <a href="https://www.techtarget.com/searchnetworking/feature/A-deep-dive-into-the-differences-between-4G-and-5G-networks">evolution of 4G</a> beyond the LTE standard. It was unclear what 5G might entail, and only pre-standard, R&D-level prototypes were in development at the time. The term B4G referred to what could be possible beyond 4G. Ironically, the LTE standard is still evolving, and 5G will use some aspects of it.</p> <p>Like B4G, Beyond 5G is seen as a path to 6G technologies that will replace fifth-generation capabilities and applications. 5G's many private wireless communications implementations involving LTE, 5G and edge computing for enterprise and industrial customers have helped lay the groundwork for 6G.</p> <p>Next-generation 6G wireless networks will take this one step further. They will create a web of communications providers -- many of them self-providers -- much in the way that photovoltaic <a href="https://www.techtarget.com/whatis/definition/solar-power">solar power</a> has brought about cogeneration within the smart grid. 6G could advance mesh networks from concept to deployment, helping to extend coverage beyond the range of older cell towers.</p> <p>Data centers are already facing significant changes driven by 5G. These include <a href="https://www.techtarget.com/searchitoperations/definition/virtualization">virtualization</a>, <a href="https://www.techtarget.com/searchnetworking/definition/programmable-network-PN">programmable networks</a>, edge computing and issues surrounding simultaneous support of public and private networks. For example, some business customers may want to combine on-premises RAN with hybrid on-premises and hosted computing -- for edge and core computing, respectively – and with data center-hosted core network elements for private business networks or alternative service providers.</p> <p>6G networks will provide the communication and data gathering necessary to accumulate information. A systems approach is required for the 6G technology market that makes use of data analytics, AI and next-generation computation capabilities with HPC and <a href="https://www.techtarget.com/whatis/definition/quantum-computing">quantum computing</a>.</p> <p>In addition to profound changes within RAN technology, 6G will bring changes to the core communications network fabric as many new <a href="https://www.techtarget.com/searchdatacenter/definition/technological-convergence">technologies converge</a>. Notably, AI will take center stage with 6G.</p> <p>6G is likely to bring several other changes:</p> <ul class="default-list"> <li><b>Nano-core.</b> A so-called nano-core is expected to emerge as a common computing core that encompasses elements of HPC and AI. The nano-core does not need to be a physical network element. Instead, it could encompass a logical collection of computational resources shared by many networks and systems.</li> <li><b>Edge and core coordination</b>. 6G networks will create substantially more data than 5G networks, and computing will evolve to include coordination between edge and core platforms. In response to those changes, data centers will have to evolve.</li> <li><b>Data management.</b> 6G capabilities in sensing, imaging and location determination will generate vast amounts of data that must be managed on behalf of the network owners, service providers and data owners.</li> <li><b>Greater energy efficiency.</b> 6G developers will focus on ensuring that the underlying hardware can function in an <a href="https://www.computerweekly.com/news/366634341/Nokia-Bell-Labs-KDDI-team-to-research-6G-energy-efficiency">energy-efficient manner</a> in the expanded frequency ranges where 6G will operate.</li> <li><b>Enhanced Ultra-Reliable Low-Latency Communication</b>. The <a href="https://www.techtarget.com/searchnetworking/definition/What-are-eMBB-URLLC-and-mMTC-in-5G-Use-cases-explained">URLLC service</a>, made possible by 5G for applications requiring very high reliability and near-real-time responsiveness, will be further enhanced with the introduction of 6G. 6G will offer higher speeds, greater network penetration and more stable performance that will further support URLLC applications like autonomous vehicles and remote surgery.</li> </ul> <p>With these enhancements, 6G is expected to support use cases that are either not possible today or only to a limited extent with existing wireless technologies. These could include the following use cases:</p> <ul class="default-list"> <li>Immersive VR and AR.</li> <li>Data-intensive and real-time <a href="https://www.techtarget.com/searchnetworking/feature/5G-and-AI-What-enterprises-need-to-know">AI workloads</a>.</li> <li>Distributed edge computing.</li> <li>Holographic communication.</li> <li>Digital twinning.</li> <li>Smart cities.</li> <li>Smart industrial automation.</li> <li>Collaborative robots.</li> <li>Synchronized distributed massive MIMO and extreme MIMO.</li> <li>Non-terrestrial networks.</li> <li>M2M communications.</li> </ul> </section> <section class="section main-article-chapter" data-menu-title="Challenges to the full realization of 6G"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Challenges to the full realization of 6G</h2> <p>6G will require the development of highly advanced mobile communications technologies, such as cognitive and highly secure data networks. It will also require the expansion of spectral bandwidth that is orders of magnitude faster than 5G. Samsung has described the need for <i>communications and computing convergence </i>-- the idea that the communication network should be designed to best use the computation power made available by the entities on that network.</p> <p>Additionally, trustworthiness will be an important consideration for 6G. Networks should be designed using a secure-by-design approach to reduce the size of the <a href="https://www.techtarget.com/whatis/definition/attack-surface">attack surface</a>. Additionally, a hardware-based secure environment and strong data protection mechanisms will be essential to safeguard data and ensure user privacy.</p> <p>Many of the problems associated with deploying millimeter-wave radio for 5G must be resolved in time for network designers to address the challenges of 6G. These 5G challenges include coverage limitations, such as the need for a line-of-sight path between transmitters and receivers, high path loss, complexities associated with small cell deployment, spectrum sharing for seamless and interference-free mobile communications, and cost-prohibitive infrastructure investments.</p> </section> <section class="section main-article-chapter" data-menu-title="What is a 7G network and why is it needed?"> <h2 class="section-title"><i class="icon" data-icon="1"></i>What is a 7G network and why is it needed?</h2> <p>6G networks are attempting to extend fast <a href="https://www.techtarget.com/searchnetworking/definition/Gigabit-Ethernet">Gigabit Ethernet</a> connectivity to commercial and consumer devices. 6G is expected to provide substantially higher throughput and data flow. As envisioned, 6G will enable the following:</p> <ul class="default-list"> <li>A theoretical data rate of about 11 Gbps simultaneously across multiple gigahertz (GHz) channels.</li> <li>Up to three 160 MHz bandwidth channels.</li> <li>Multiplex up to eight spatial streams.</li> </ul> <p>In 2020, the FCC was the first regulatory body to greenlight the 6 GHz spectrum to help foster innovation of 6G devices.</p> <p>Although 6G networks are not expected to be operational until at least 2032, research has already begun on the 6G successor: seventh-generation (7G) wireless technologies. The <a href="https://www.techtarget.com/whatis/definition/IEEE-Institute-of-Electrical-and-Electronics-Engineers">IEEE</a>, through its Extremely High Throughput working group, is developing the <a href="https://www.techtarget.com/searchnetworking/definition/Wi-Fi-7">802.11be specification</a> for 7G and an industry certification in conjunction with the Wi-Fi Alliance. The project’s goal is to enable wireless communications with extremely high throughput while reducing worst-case latency. The standard also aims to ensure that 7G will be backward compatible with legacy devices operating in the 2.4 GHz, 5 GHz and 6 GHz bands.</p> <p>Compared to 6G, 7G is designed to do the following:</p> <ul class="default-list"> <li>Deliver data up to 46 Gbps -- more than four times the rate of 6G projection.</li> <li>Double the size of the channel to 320 MHz.</li> <li>Afford 16 spatial streams, compared to eight in 6G.</li> </ul> <figure class="main-article-image half-col" data-img-fullsize="https://www.techtarget.com/rms/onlineimages/6g_vs_7g_expectations-h.png"> <img data-src="https://www.techtarget.com/rms/onlineimages/6g_vs_7g_expectations-h_half_column_mobile.png" class="lazy" data-srcset="https://www.techtarget.com/rms/onlineimages/6g_vs_7g_expectations-h_half_column_mobile.png 960w,https://www.techtarget.com/rms/onlineimages/6g_vs_7g_expectations-h.png 1280w" alt="Table comparing 6G and 7G expectations for data rates, bandwidth channels and spatial streams." height="244" width="279"> <figcaption> <i class="icon pictures" data-icon="z"></i>Early work on 7G technology projects has made great advances in speed, bandwidth and spatial streams compared to 6G. </figcaption> <div class="main-article-image-enlarge"> <i class="icon" data-icon="w"></i> </div> </figure> <p>7G technology will represent a quantum leap in bandwidth to support ultra-dense workloads. For example, 7G has the potential to enable continuous global wireless connectivity via integration in <a href="https://www.techtarget.com/searchnetworking/tip/An-introduction-to-satellite-network-architecture">satellite networks</a> for Earth imaging, telecom and navigation. Enterprises could implement 7G to automate manufacturing processes and support applications that require high availability, predictable latency or guaranteed quality of service.</p> <p>6GE -- the "E" stands for <i>extension</i> -- is an interim step between 6G and 7G that will use a newly licensed 6 GHz channel that extends the available frequencies used to transmit 6G signals.</p> <p><i>Learn about the state of wireless networking today with our </i><a href="https://www.techtarget.com/searchnetworking/Enterprise-5G-Guide-to-planning-architecture-and-benefits"><i>guide to 5G technology and planning</i></a><i> and </i><a href="https://www.techtarget.com/whatis/feature/5-Predictions-about-5G-Adoption-in-2021-and-Beyond"><i>predictions related to 5G adoption</i></a><i>.</i></p> </section> 6G (sixth-generation wireless) is the successor to 5G cellular technology and is expected to be globally available by around 2030. https://cdn.ttgtmedia.com/visuals/digdeeper/2.jpg https://www.techtarget.com/searchnetworking/definition/6G Fri, 21 Nov 2025 13:30:00 GMT What is 6G? Overview of 6G networks & technology <p>Identity and access management, or IAM, is a framework of business processes, policies and technologies that facilitates the management of digital identities. With an IAM framework in place, IT security teams can control user access to critical information within their organizations.</p> <p>Using methods such as single sign-on (<a href="https://www.techtarget.com/searchsecurity/definition/single-sign-on">SSO</a>), <a href="https://www.techtarget.com/searchsecurity/definition/two-factor-authentication">two-factor authentication</a> and <a href="https://www.techtarget.com/searchsecurity/definition/privileged-access-management-PAM">privileged access management</a>, IAM technologies securely store identity and profile data and manage data governance functions to ensure that only necessary and relevant data is shared.</p> <p>IAM performs the following fundamental security actions:</p> <ul class="default-list"> <li>Identifies individuals in a system through <a href="https://www.techtarget.com/searchsecurity/answer/Authentication-vs-digital-identity-Whats-the-difference">identity management and authentication</a>.</li> <li>Identifies roles in a system and how roles are assigned to individuals.</li> <li>Adds, removes and updates individuals and their roles in a system.</li> <li>Assigns levels of access to individuals or groups of individuals.</li> <li>Protects sensitive data within the system and secures the system itself.</li> </ul> <p>An enterprise's ability to know who is accessing which data and which systems and from where is not only helpful but critical to data protection. Employees are in far-flung locales, sometimes in branch offices and sometimes working remotely from their homes. Traditional defenses built around a known perimeter are no longer adequate, which is one reason why cybersecurity experts now refer to identity as the new perimeter.</p> <p>This comprehensive guide examines the many aspects of identity and access management, including its challenges, technologies and trends. Hyperlinks direct readers to related articles that provide additional insights and guidance about how to understand, implement and manage IAM.</p> <figure class="main-article-image full-col" data-img-fullsize="https://www.techtarget.com/rms/onlineImages/security-iam_risk_analytics-f.png"> <img data-src="https://www.techtarget.com/rms/onlineImages/security-iam_risk_analytics-f_mobile.png" class="lazy" data-srcset="https://www.techtarget.com/rms/onlineImages/security-iam_risk_analytics-f_mobile.png 960w,https://www.techtarget.com/rms/onlineImages/security-iam_risk_analytics-f.png 1280w" alt="Graphic showing how an IAM system analyzes user behavior." height="321" width="560"> <div class="main-article-image-enlarge"> <i class="icon" data-icon="w"></i> </div> </figure> <section class="section main-article-chapter" data-menu-title="Why is IAM important?"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Why is IAM important?</h2> <p>Business leaders and IT departments are under pressure to grant access to corporate resources while at the same time protecting those resources. It's a balancing act, and it's not a simple one. Security teams must assign and track user privileges so that users can work with the data and applications they need to be productive -- without being so lax that bad actors find their way into systems.</p> <p>The increased adoption of cloud services and the growth in hybrid and remote workforces mean more users are accessing more applications from more locations. These conditions make proper identity management indispensable.</p> <p>Cybersecurity relies on IAM and its ever-increasing list of features, including <a href="https://www.techtarget.com/searchsecurity/definition/biometrics">biometrics</a>, behavior analytics and AI. With its tight control of resource access in highly distributed and dynamic environments, IAM aligns with security's transition from using traditional firewalls and inherent-trust practices to more rigid control architectures.</p> <p>The foremost of these stricter controls is the <a href="https://www.techtarget.com/searchsecurity/definition/zero-trust-model-zero-trust-network">zero-trust model</a>. An organization that implements zero trust authorizes and authenticates users continuously, not merely once at the perimeter. This inverts the idea that users who've been cleared can be fully trusted. The zero-trust architecture prevents unnecessary movement between applications and systems, which, in turn, limits the damage an intruder might do.</p> <p>With IAM in place, an organization gives itself important capabilities for heightened control over managing users' access in an organized fashion. Automation features eliminate manual steps, which boosts efficiency and lowers the chance of human error.</p> <p>Businesses that are inattentive to IAM run the risk of intrusion, data loss, ransom attacks and worse. Bad actors often use stolen credentials to impersonate valid users. Because this access appears legitimate, cybercriminals can misuse credentials to linger inside a network for extended periods. If the stolen credential can be used to gain administrator privileges, the data loss and potential damage can be considerable. Bad actors use a range of tactics, including phishing and vishing, to acquire credentials.</p> <p>Research by Verizon found that, over the past decade, stolen credentials have played a role in nearly one-third of breaches. Credential theft is so effective that it is used by both run-of-the-mill cybercriminals and highly organized nation-state threat actors.</p> <div class="youtube-iframe-container"> <iframe id="ytplayer-0" src="https://www.youtube.com/embed/D6nql-FGAyk?autoplay=0&modestbranding=1&rel=0&widget_referrer=null&enablejsapi=1&origin=https://www.techtarget.com" type="text/html" height="360" width="640" frameborder="0" loading="lazy"></iframe> </div> </section> <section class="section main-article-chapter" data-menu-title="Basic components of IAM"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Basic components of IAM</h2> <p>IAM products offer access control, which lets system administrators regulate access to systems or networks based on the roles of individual users within the enterprise.</p> <p>In this context, <i>access</i> is the ability of an individual user to perform a specific task, such as view, create or modify a file. Roles are defined according to job, authority and responsibility. <a href="https://www.techtarget.com/searchsecurity/tip/Types-of-access-control">Key types of access control</a> include the following:</p> <ul class="default-list"> <li>Role-based access control.</li> <li>Discretionary access control.</li> <li>Attribute-based access control.</li> <li>Mandatory access control.</li> </ul> <p>To gain access to those authorized resources, users must prove they are who they say they are. This is a complicated but necessary component of IAM, typically involving passwords, <a href="https://www.techtarget.com/searchsecurity/definition/challenge-response-system">challenge-response authentication</a> and related methods.</p> <p>IAM systems should capture and record user login information, manage the enterprise database of user identities and orchestrate the assignment and removal of access privileges. Tools used for IAM should provide a centralized directory service with oversight and visibility into all aspects of the company user base.</p> <p>To ensure the effectiveness of their IAM efforts, security teams should look to various identity standards and protocols. These tried-and-true standards can help improve an organization's security posture, compliance efforts and even user experience. The <a href="https://www.techtarget.com/searchsecurity/definition/authentication-authorization-and-accounting">authentication, authorization and accounting</a> framework, for example, is a way for security teams to organize their IAM work. It provides structure for access control, policy enforcement and usage tracking.</p> <p>Another way for a business to manage IAM is the use of <a href="https://www.techtarget.com/searchsecurity/definition/identity-governance-and-administration-IGA">identity governance and administration</a>, which is a collection of processes that help ensure proper installation, oversight, enforcement and auditing of IAM policies.</p> <p>It's worth remembering that a <a href="https://www.techtarget.com/whatis/definition/digital-identity">digital identity</a> isn't just for a person. IAM can and should manage the digital identities of devices and applications -- what's often called <i><a href="https://www.techtarget.com/searchsecurity/definition/What-is-machine-identity-management">machine identity management</a></i> or <i>nonhuman identity management</i>. These can be APIs, servers and devices that access information and need to be managed. Security experts say organizations have begun to realize just how many of these identities are present in their environments. Working to secure them is one of the emerging trends in IAM.</p> </section> <section class="section main-article-chapter" data-menu-title="Benefits of IAM"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Benefits of IAM</h2> <p>IAM technologies can be used to initiate, capture, record and manage user identities and their related access permissions in an automated manner. In an era when workforces are more geographically scattered than ever before, well-operated IAM takes on greater importance.</p> <p>An organization with an effective IAM program should expect to see the following benefits, <a href="https://www.techtarget.com/searchsecurity/answer/What-are-the-key-identify-and-access-management-benefits">among other advantages</a>:</p> <ul class="default-list"> <li>Access privileges being granted according to policy, with all individuals and services properly authenticated, authorized and audited.</li> <li>Control of user access, which reduces the risk of internal and external data breaches.</li> <li>Enforcement of policies around user <a href="https://www.techtarget.com/searchsecurity/definition/authentication">authentication</a>, validation and privileging.</li> <li>Better compliance with government regulations.</li> </ul> <p>IAM implementation is necessary for secure operations, but companies can also gain competitive advantages. For example, IAM technologies enable a business to give users outside the organization -- such as customers, partners, contractors and suppliers -- access to applications and data without compromising security.</p> <div class="youtube-iframe-container"> <iframe id="ytplayer-1" src="https://www.youtube.com/embed/TbTUw2oz0EM?autoplay=0&modestbranding=1&rel=0&widget_referrer=null&enablejsapi=1&origin=https://www.techtarget.com" type="text/html" height="360" width="640" frameborder="0" loading="lazy"></iframe> </div> </section> <section class="section main-article-chapter" data-menu-title="IAM technologies and tools"> <h2 class="section-title"><i class="icon" data-icon="1"></i>IAM technologies and tools</h2> <p>IAM technologies are designed to simplify the user provisioning and account setup process. These systems should reduce the time it takes to complete these processes with a controlled workflow that decreases errors and the potential for abuse while enabling automated account fulfillment. An IAM system should also allow administrators to instantly view and change evolving access roles and rights.</p> <p>These systems should balance the speed and automation of their processes with the control that administrators need to monitor and modify access rights. Consequently, to manage access requests, the central directory needs an access rights system that automatically matches employee job titles, business unit identifiers and locations to their relevant privilege levels.</p> <p>Multiple review levels can be included as workflows to enable the proper checking of individual requests. This simplifies setting up appropriate review processes for higher-level access. It also eases reviews of existing rights to prevent privilege creep, which is the gradual accumulation of access rights beyond what users need to do their jobs.</p> <p>A good IAM tool will automate least-privilege provisioning, enable SSO across multiple apps and providers, provide broad access visibility into an organization's systems and deliver a reasonably smooth user experience, among other functions.</p> <p>IAM systems should be used to provide flexibility to establish groups with specific privileges for specific roles so that access rights based on employee job functions can be uniformly assigned. The system should also provide request and approval processes for modifying privileges, as employees with the same title and job location might need customized or slightly different access.</p> <p>With IAM, enterprises can <a href="https://www.techtarget.com/searchsecurity/answer/What-are-the-most-common-digital-authentication-methods">implement a range of digital authentication methods</a> to prove digital identity and authorize access to corporate resources.</p> <p><b>Unique passwords.</b> The most common type of digital authentication continues to be the unique password. While not especially secure or convenient, passwords are typically how users access their accounts for shopping, banking, entertainment, email and work.</p> <p>To make passwords more secure, some organizations require longer or more complex passwords that include a combination of letters, symbols and numbers. Users understandably find it onerous to remember which long and complex password will get them logged in to this app or that site. SSO entry points and <a href="https://www.techtarget.com/searchsecurity/definition/password-manager">password managers</a> can help alleviate that burden.</p> <p><b>Multifactor authentication.</b> <a href="https://www.techtarget.com/searchsecurity/definition/multifactor-authentication-MFA">MFA</a> is an increasingly common type of authentication. An IAM system that requires a user to enter a code texted to their phone, for example, increases the likelihood that the access attempt is legitimate. Unless they've already gained access to -- or possession of -- the user's phone, bad actors with a stolen password won't be able to clear that second authentication hurdle.</p> <p>The MFA movement is gaining momentum. Employers now routinely ask remote workers to use a second or third factor to prove their identity. Financial institutions and other security-minded organizations use MFA processes before granting a customer access to an account. In 2024, Google Cloud, AWS and Microsoft Azure all decided that they will require MFA for their customers to access cloud services.</p> <div class="youtube-iframe-container"> <iframe id="ytplayer-2" src="https://www.youtube.com/embed/_3rlQVXGKZc?autoplay=0&modestbranding=1&rel=0&widget_referrer=null&enablejsapi=1&origin=https://www.techtarget.com" type="text/html" height="360" width="640" frameborder="0" loading="lazy"></iframe> </div> <p><b>Adaptive authentication.</b> When dealing with highly sensitive information and systems, organizations can use behavioral or adaptive authentication methods to assist in identity management. IAM tools, for example, are now more capable of noticing when someone who typically logs in from a certain place at a certain time is attempting to access systems from another location and at a time they are not normally working. These behaviors could signal that the user's credentials have been compromised.</p> <p>By applying AI, organizations can more readily recognize if user or machine behavior falls outside of the norm; anomalies should trigger automatic lockdowns.</p> <p><b>Biometrics.</b> Some IAM systems use biometrics as their method of authentication. Biometric characteristics, such as fingerprints, irises, faces, palms, gaits, voices and, in some cases, DNA, are seen as an easy and precise way to know exactly who is accessing what.</p> <p>While the convenience of facial recognition or fingerprint scanning is hard to deny, the use of biometrics involves risks -- ones that are unlike other challenges in IT or security. Stolen fingerprint data, for example, can't be replaced the way a hacked password can be. Make sure to fully understand the <a href="https://www.techtarget.com/searchsecurity/tip/Evaluate-biometric-authentication-pros-and-cons-implications">pros and cons of biometric authentication</a>.</p> <p>When an organization collects a person's specific facial characteristics, it assumes the serious responsibility of safeguarding that data. Organizations with plans to adopt biometrics need to work through a <a href="https://www.techtarget.com/searchsecurity/tip/In-biometrics-security-concerns-span-technical-legal-and-ethical">long list of privacy and legal questions</a> before committing to this form of authentication.</p> <figure class="main-article-image full-col" data-img-fullsize="https://www.techtarget.com/rms/onlineimages/security-biometric_authentication_types.png"> <img data-src="https://www.techtarget.com/rms/onlineimages/security-biometric_authentication_types_mobile.png" class="lazy" data-srcset="https://www.techtarget.com/rms/onlineimages/security-biometric_authentication_types_mobile.png 960w,https://www.techtarget.com/rms/onlineimages/security-biometric_authentication_types.png 1280w" alt="An illustration of 16 types of biometric authentication." height="608" width="559"> <div class="main-article-image-enlarge"> <i class="icon" data-icon="w"></i> </div> </figure> </section> <section class="section main-article-chapter" data-menu-title="Implementing IAM in the enterprise"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Implementing IAM in the enterprise</h2> <p>A key area of concern in IAM is <a href="https://www.techtarget.com/searchsecurity/tip/User-provisioning-and-deprovisioning-Why-it-matters-for-IAM">how accounts are provisioned and deprovisioned</a>.</p> <p>IT teams will sometimes grant privileges to a user beyond what's needed for that person to do a particular job. For an intruder, these overprivileged accounts are especially valuable targets because they allow access to many parts of an organization. A related risk is poor deprovisioning practices, or the removal of access when a specific employee changes roles or leaves the company. Strict provisioning also reduces the chances of an insider threat.</p> <p>An organization needs to identify a team of people who will play a lead role in the enforcement of identity and access policies. IAM affects every department and every type of user -- employee, contractor, partner, supplier, customer and so on -- so it's essential the IAM team comprises a mix of corporate functions. An approach that pulls together various people and is organized around the same goals should improve the chances of success in identity security.</p> <p>What's needed for an <a href="https://www.techtarget.com/searchsecurity/feature/How-to-build-an-identity-and-access-management-architecture">effective IAM infrastructure</a>? Key points to evaluate include how to handle authentication and <a href="https://www.techtarget.com/searchsecurity/definition/federated-identity-management">federated identity management</a>. These activities could involve a decision to use the <a href="https://www.techtarget.com/whatis/definition/OpenID">OpenID Connect</a> protocol or the <a href="https://www.techtarget.com/searchsecurity/definition/SAML">SAML</a> standard, which are similar but not the same.</p> <p>Implementations should be carried out with <a href="https://www.techtarget.com/searchsecurity/tip/Best-practices-for-a-bulletproof-IAM-strategy">IAM best practices</a> in mind, which include the following:</p> <ul class="default-list"> <li>Adoption of the zero-trust architecture.</li> <li>Use of MFA.</li> <li>Strong password policies.</li> <li>Promotion of security awareness training.</li> </ul> <p>Businesses also should make sure to centralize security and critical systems around identity. Perhaps most importantly, organizations should create a process they can use to evaluate the efficacy of current IAM controls.</p> <p>While IAM relies on a lot of technology, it is not about only the frameworks and tools. An IT security team needs people who possess <a href="https://www.techtarget.com/searchsecurity/tip/What-skills-are-needed-for-a-successful-career-in-IAM">IAM skills and expertise</a>. Those seeking jobs in the field should be ready to demonstrate their knowledge when it comes time for <a href="https://www.techtarget.com/whatis/feature/IAM-Interview-Questions-and-Answers">the IAM job interview</a>.</p> <figure class="main-article-image full-col" data-img-fullsize="https://www.techtarget.com/rms/onlineimages/mfa_sms_examples-f.png"> <img data-src="https://www.techtarget.com/rms/onlineimages/mfa_sms_examples-f_mobile.png" class="lazy" data-srcset="https://www.techtarget.com/rms/onlineimages/mfa_sms_examples-f_mobile.png 960w,https://www.techtarget.com/rms/onlineimages/mfa_sms_examples-f.png 1280w" alt="Graphic of two smartphones displaying examples of MFA messages. " height="353" width="560"> <div class="main-article-image-enlarge"> <i class="icon" data-icon="w"></i> </div> </figure> </section> <section class="section main-article-chapter" data-menu-title="IAM risks"> <h2 class="section-title"><i class="icon" data-icon="1"></i>IAM risks</h2> <p>While essential to security efforts, IAM is not without risks. Organizations can -- and do -- get things wrong when trying to manage identities and control access.</p> <p>Access management can be of concern when the provisioning and deprovisioning of user accounts aren't handled correctly. Security teams need to be aware of vulnerable, inactive user accounts. When there is a sprawl in admin accounts, someone should notice and raise questions about why. Organizations need to ensure lifecycle control over all aspects of IAM to prevent malicious actors from gaining access to user identities and passwords.</p> <p>Specific <a href="https://www.techtarget.com/searchsecurity/answer/What-are-some-of-the-top-identity-and-access-management-risks">IAM risks to watch for</a> include the following:</p> <ul class="default-list"> <li>Irregular access reviews.</li> <li>Weak passwords and missing MFA.</li> <li>Overprivileged accounts.</li> <li>Poorly integrated IAM across systems and clouds.</li> </ul> <p>Audit capabilities act as a check to ensure users' access changes accordingly when they switch roles or leave the organization.</p> <p>To better assess their organization's security risks, IT professionals can pursue security certifications. Some certifications are <a href="https://www.techtarget.com/searchsecurity/tip/Comparing-top-identity-and-access-management-certifications">specific to identity management</a>.</p> </section> <section class="section main-article-chapter" data-menu-title="IAM vendors and products"> <h2 class="section-title"><i class="icon" data-icon="1"></i>IAM vendors and products</h2> <p>IAM vendors range from large companies -- such as IBM, Microsoft, Oracle and RSA -- to pure-play providers -- such as Okta, Ping Identity, SailPoint and OneLogin.</p> <p>The dynamic nature of <a href="https://www.techtarget.com/searchsecurity/feature/8-leading-identity-and-access-management-products-for-2020">the IAM tools market</a> means that organizations have plenty of options. It also means security teams will need to do some legwork to identify the right mix of products that will address the needs of the business, such as centralized management, SSO, governance, compliance and risk analytics tools.</p> <p>Some vendors are moving toward combining various products and tooling into IAM platforms. Having a suite of capabilities in a single platform could lessen the integration problems found with the currently fragmented market of IAM products.</p> </section> <section class="section main-article-chapter" data-menu-title="IAM and compliance"> <h2 class="section-title"><i class="icon" data-icon="1"></i>IAM and compliance</h2> <p>Central to IAM is an adherence to the <a href="https://www.techtarget.com/searchsecurity/definition/principle-of-least-privilege-POLP">principle of least privilege</a>, where users are granted only the access rights necessary to fulfill their particular work duties. This predetermined and real-time access control is necessary for security as well as compliance.</p> <p>With IAM controls in place, a business should be able to prove to outside entities that it takes its security responsibilities seriously and that data is protected. Organizations with effective IAM can <a href="https://www.techtarget.com/searchsecurity/tip/Identity-management-compliance-How-IAM-systems-support-compliance">demonstrate compliance</a> and adhere to applicable regulations, such as GDPR, HIPAA and the Sarbanes-Oxley Act.</p> </section> <section class="section main-article-chapter" data-menu-title="The IAM roadmap"> <h2 class="section-title"><i class="icon" data-icon="1"></i>The IAM roadmap</h2> <p>Innovation is plentiful around IAM, and enterprises are the beneficiaries of new strategies that are backed up by products and features. As has always been the case, however, security professionals must confront threats that are known -- and persistent because of their proven effectiveness -- and ones that are emerging and less defined.</p> <p>One of the newer IAM-related defenses against cyberattacks is identity threat detection and response (<a href="https://www.techtarget.com/searchsecurity/definition/What-is-identity-threat-detection-and-response-ITDR">ITDR</a>). A combination of tools and best practices, ITDR is intended to stop bad actors from taking advantage of vulnerable identities, such as one associated with a legacy application that isn't compatible with a modern access management tool. ITDR can flag these weaknesses, giving an IT team the chance to address the vulnerabilities before they are exploited.</p> <p>Advancements in AI have heightened concerns about identity security. Experts worry that <a href="https://www.techtarget.com/searchsecurity/tip/Generative-AI-is-making-phishing-attacks-more-dangerous">AI could make phishing tactics more sophisticated</a> and more believable. Effective phishing typically requires some morsel of information that lends at least a ring of truth to the message -- something that sounds reasonable enough to trick a recipient into action. AI can quickly and efficiently gather the bits of information that provide that veneer of legitimacy.</p> <blockquote class="main-article-pullquote"> <div class="main-article-pullquote-inner"> <figure> Longer, stronger passwords might improve identity management, but they won't satisfy those who would like to see every password permanently expire. </figure> <i class="icon" data-icon="z"></i> </div> </blockquote> <p>When cybercriminals can induce their victims to click a link or reveal a password, even strong organizational defenses and IAM protections can be thwarted.</p> <p>Even without AI's help, passwords have long been vulnerable. Cracking techniques make many passwords solvable. And the prospect of needing to create and remember yet another password is a common aggravation. It's fair to say passwords are about as popular with hackers as they are unpopular with users.</p> <p>Despite being both risky and unloved, passwords endure. The shift to <a href="https://www.techtarget.com/searchsecurity/definition/passwordless-authentication">passwordless authentication</a> is tantalizing, but that passwordless future has yet to arrive.</p> <p>In a September 2024 earnings call, Oracle's chairman and cofounder Larry Ellison lamented tech's continued reliance on passwords. Ellison argued that facial recognition tools should be the way forward. "Look at me and recognize me," Ellison said. "Don't ask me to type in some stupid 17-letter password."</p> <p>Ellison's remarks came at roughly the same time that NIST, which sets the most widely accepted cybersecurity standards, proposed significant adjustments to its password guidelines. Recognizing that passwords are still widely used and likely will be for the foreseeable future, NIST is advocating for better passwords. The 2024 draft guidelines call for organizations to eliminate the common mandate for users to reset a password every 90 days; a password change, NIST suggested, should be made only when there's evidence or reasonable concern that a breach has compromised someone's credentials. The NIST proposal also recommended password length grow to between 15 and 64 characters.</p> <p>Longer, stronger passwords might improve identity management, but they won't satisfy those who would like to see every password permanently expire. Promoters of passkeys, for example, argue that users should be able to access applications and websites with the same safe and simple methods they use to unlock a device. Once a passkey is created, password-manager technology matches a public key known only to the service being accessed with a private key known only to the device being used. This cryptographic key pair lets users authenticate themselves without needing to remember a password -- provided they have securely unlocked the device in use through a PIN or biometric method.</p> <p>The FIDO Alliance, a nonprofit with backing from Google and others, is <a href="https://www.passkeycentral.org/introduction-to-passkeys/the-passkey-experience" target="_blank" rel="noopener">pushing standards</a> that would enable wider use of passkeys. The goal would be to effectively replace passwords. Whether businesses and individuals will embrace passkeys and password managers is far from certain. And it's worth remembering that the password's demise has been sought -- and predicted -- for a long time, which gives you something to think about the next time you stop to remember how to sign in to your account.</p> <p><i>Phil Sweeney is an industry editor and writer focused on information security topics. Article was updated in 2025 to improve the reader's experience.</i></p> </section> No longer just a good idea, IAM is a crucial piece of the cybersecurity puzzle. It's how an organization regulates access to information and meets its compliance obligations. https://cdn.ttgtmedia.com/visuals/digdeeper/4.jpg https://www.techtarget.com/searchsecurity/definition/identity-access-management-IAM-system Fri, 21 Nov 2025 00:00:00 GMT What is identity and access management? Guide to IAM <p>A chief data officer (CDO) in many organizations is a <a href="https://www.techtarget.com/searchcio/definition/C-level">C-level</a> executive whose position has evolved into a range of strategic data management responsibilities, including <a href="https://www.techtarget.com/searchdatamanagement/definition/data-governance">data governance</a>, data quality and data strategy. The CDO's role is to derive maximum value from the data available to the enterprise.</p> <p>CDO is one of the relatively newer positions within an organization's leadership ranks, and the role is evolving. The CDO's responsibilities have expanded beyond liberating data silos and <a href="https://www.techtarget.com/searchsecurity/tip/How-to-overcome-GDPR-compliance-challenges">complying with various data protection and privacy regulations</a>. The CDO must support digital transformation, harnessing advanced technologies to gain valuable insights and monetize data collected from multiple sources. The CDO's role can entail data science, analytics, business processes, marketing initiatives, product development, supply chains, and customer and employee engagements.</p> <p>Depending on the organization, the definition and responsibilities of a CDO, chief digital officer and chief analytics officer (CAO) can overlap, with boundary lines blurred among the three. The CDO often reports to the chief executive officer (<a href="https://www.techtarget.com/searchcio/definition/CEO">CEO</a>) but also frequently reports to chief operating officer (<a href="https://www.techtarget.com/searchcio/definition/Chief-Operating-Officer-COO">COO</a>) or chief financial officer (<a href="https://www.techtarget.com/searchcio/definition/CFO">CFO</a>). Less frequently, the CDO might report to the chief technology officer (<a href="https://www.techtarget.com/searchcio/definition/Chief-Technology-Officer-CTO">CTO</a>) or chief information officer (<a href="https://www.techtarget.com/searchcio/definition/CIO">CIO</a>).</p> <p>In many organizations, the CDO also works closely with the chief marketing officer (<a href="https://www.techtarget.com/searchcio/definition/CMO-chief-marketing-officer">CMO</a>) to use data to improve customer interactions, support an optimal customer experience and ultimately drive sales.</p> <p>Researchers and management consultants believe the most effective organizations assign clearly defined responsibilities for the CDO, CIO and other executive leadership positions that interact with and support the <a href="https://www.techtarget.com/searchdatamanagement/feature/How-VMwares-CDO-views-data-management">organization's data management programs</a>.</p> <figure class="main-article-image full-col" data-img-fullsize="https://www.techtarget.com/rms/cio/business_analytics-chief_data_officer.jpg"> <img data-src="https://www.techtarget.com/rms/cio/business_analytics-chief_data_officer_mobile.jpg" class="lazy" data-srcset="https://www.techtarget.com/rms/cio/business_analytics-chief_data_officer_mobile.jpg 960w,https://www.techtarget.com/rms/cio/business_analytics-chief_data_officer.jpg 1280w" alt="An infographic detailing the evolution of the CDO role." height="437" width="520"> <figcaption> <i class="icon pictures" data-icon="z"></i>As businesses digitally transform, so does the evolving role of CDOs. </figcaption> <div class="main-article-image-enlarge"> <i class="icon" data-icon="w"></i> </div> </figure> <section class="section main-article-chapter" data-menu-title="Role of the chief data officer"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Role of the chief data officer</h2> <p>The CDO has senior-most responsibility for the organization's <a href="https://www.techtarget.com/searchcio/definition/strategic-management">strategic use of data</a>, so the enterprise can perform more efficiently, boost productivity, better engage with customers, employees and other stakeholders, improve existing revenue streams and create new ones, and develop new business opportunities.</p> <p>The CDO is expected to perform these tasks by using various tools and technologies, including <a href="https://www.techtarget.com/searchcio/tip/10-ways-to-use-machine-learning-and-AI-in-ITSM-to-improve-processes">AI, machine learning</a>, the cloud, internet of things (<a href="https://www.computerweekly.com/news/366632647/AI-becomes-major-accelerator-for-IoT">IoT</a>), advanced analytics and <a href="https://www.techtarget.com/searchbusinessanalytics/definition/business-intelligence-BI">business intelligence</a> software. An equally important aspect of the CDO role is building a team of data professionals who understand the organization's culture, objectives and industry, so they can apply data analysis to address concerns, challenges, risks and opportunities.</p> <p>Additionally, the CDO is responsible for establishing and maintaining the organization's <a href="https://www.techtarget.com/searchcio/definition/data-governance-policy">data governance policy</a> and procedures, ensuring lifecycle data quality and management. These tasks require the CDO to cooperate with C-suite executives. The CDO is also expected to work closely with executive colleagues whose responsibilities involve data. These colleagues might include the chief information security officer (<a href="https://www.techtarget.com/searchsecurity/definition/CISO-chief-information-security-officer">CISO</a>) charged with ensuring data security within the organization, or the legal, compliance and risk leaders tasked with ensuring the organization's data policies comply with applicable rules and regulations.</p> <div class="youtube-iframe-container"> <iframe id="ytplayer-0" src="https://www.youtube.com/embed/3GkFDP_fwkY?autoplay=0&modestbranding=1&rel=0&widget_referrer=null&enablejsapi=1&origin=https://www.techtarget.com" type="text/html" height="360" width="640" frameborder="0" loading="lazy"></iframe> </div> </section> <section class="section main-article-chapter" data-menu-title="Key CDO areas of responsibility"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Key CDO areas of responsibility</h2> <p>The chief data officer's <a href="https://www.techtarget.com/searchdatamanagement/ehandbook/Chief-data-officer-challenges-mount-amid-calls-for-more-value">responsibilities have expanded significantly</a> as data management takes on greater importance for organizations in the throes of digital transformation and relying on business intelligence to continue competing at a high level.</p> <p>Here are some of the data-related areas that can come under the CDO's purview and affect virtually every aspect of an enterprise, including customers, employees and third-party stakeholders:</p> <ul class="default-list"> <li>Overseeing the management and flow of data throughout its lifecycle.</li> <li>Managing data governance strategies, practices and requirements.</li> <li>Organizing, storing and analyzing strategic, operational and production data.</li> <li>Establishing corporate practices that comply with data protection and privacy regulations.</li> <li>Designing, developing and maintaining <a href="https://www.techtarget.com/whatis/feature/Who-manages-data-lakes-and-what-skills-are-needed">data warehouses and other repositories</a>.</li> <li>Ensuring business intelligence systems meet organizational requirements.</li> <li>Implementing <a href="https://www.techtarget.com/searchcio/tip/7-business-process-management-challenges-and-how-to-fix-them">data analytics effectively into business processes</a>.</li> <li>Prioritizing data quality initiatives that support accurate business outcomes.</li> <li>Establishing mechanisms that <a href="https://www.computerweekly.com/feature/Why-some-data-driven-decisions-are-not-to-be-trusted">ensure the trustworthiness of data</a>.</li> <li>Improving user access to data while ensuring data protection and privacy.</li> <li>Promoting data democratization, data literacy and a <a href="https://www.techtarget.com/searchdatamanagement/definition/DataOps">DataOps</a> culture companywide.</li> <li><a href="https://www.computerweekly.com/news/252514852/Siloed-data-holding-back-coordinated-health-responses">Liberating siloed data</a> that hinders intradepartmental business initiatives.</li> <li>Monetizing data collected from multiple sources by using advanced technologies.</li> <li>Supporting the development and marketing of new products and services.</li> </ul> </section> <section class="section main-article-chapter" data-menu-title="Why CDOs are needed"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Why CDOs are needed</h2> <p>Gartner defines today's CDO as a "senior executive who bears responsibility for the firm's enterprise-wide data and information strategy, governance, control, policy development and effective exploitation … to create business value."</p> <p>Organizations of all kinds realize they can use business intelligence and analytics tools to <a href="https://www.techtarget.com/searchdatamanagement/ehandbook/Enterprise-data-lakes-hold-the-key-to-actionable-insights">mine structured and unstructured data for insights</a> into their business, industry and customers as well as market dynamics and consumer buying patterns.</p> <figure class="main-article-image full-col" data-img-fullsize="https://www.techtarget.com/rms/onlineimages/snapshot_of_todays_cdo-f.png"> <img data-src="https://www.techtarget.com/rms/onlineimages/snapshot_of_todays_cdo-f_mobile.png" class="lazy" data-srcset="https://www.techtarget.com/rms/onlineimages/snapshot_of_todays_cdo-f_mobile.png 960w,https://www.techtarget.com/rms/onlineimages/snapshot_of_todays_cdo-f.png 1280w" alt="A bar chart showing the relative frequency of more than a dozen key CDO responsibilities." height="426" width="560"> <figcaption> <i class="icon pictures" data-icon="z"></i>CDOs typically have a range of responsibilities but are mainly focused on generating revenue from data. </figcaption> <div class="main-article-image-enlarge"> <i class="icon" data-icon="w"></i> </div> </figure> <p>Leading executives understand that <a href="https://www.techtarget.com/searchdatamanagement/tip/Business-shift-to-a-data-monetization-strategy-elevates-CDOs">data-driven insights can be monetized</a> to improve their organization's performance by streamlining business operations, increasing productivity, managing remote and hybrid workforces, improving customer experiences and developing new products and services.</p> <p>More recently, enterprise leaders have come to see data and the ability to mine it for insights and intelligence as critical to driving <a href="https://www.techtarget.com/searchcio/definition/digital-transformation">digital transformation</a> and competing in the digital marketplace.</p> <p>Digitally savvy enterprises see data as an indispensable asset that requires the management and expertise of a senior-level executive who's responsible for setting the data strategy companywide.</p> </section> <section class="section main-article-chapter" data-menu-title="CDO vs. CAO vs. CIO"> <h2 class="section-title"><i class="icon" data-icon="1"></i>CDO vs. CAO vs. CIO</h2> <p>Like the CDO and chief digital officer roles, there often is a blurring of lines between <a href="https://www.techtarget.com/searchbusinessanalytics/feature/Chief-data-and-analytics-officer-roles-What-you-need-to-know">CDO and CAO responsibilities</a>. <a href="https://www.techtarget.com/searchbusinessanalytics/feature/Chief-data-and-analytics-officer-roles-What-you-need-to-know"></a>Some research firms will often provide statistics related to the chief data/analytics officer.</p> <p>The CDO's core responsibilities are the management, flow and strategy of data throughout its lifecycle to meet the company's business and financial objectives, while the CAO's core responsibilities focus on the analysis of that data to meet the organization's business, operational and customer analytics needs. Depending on the company's size and industry, those roles can command separate titles or be combined into one title.</p> <p>The CDO is expected to collaborate with other executives on data-driven initiatives and the analysis of data. In some organizations, data analysis is the responsibility of the CAO, along with other tasks similar to the CDO, including data strategy, treating data as an asset and deriving value from data. The CAO often reports to the CEO, but the position sometimes reports to the CDO. However, many organizations might not have a CAO or lack both a CDO and CAO.</p> <p>The CDO position is related to, but separate from, the <a href="https://www.techtarget.com/searchcio/cio-role">job of the CIO</a>. The CIO generally provides and supports the technology needed to collect, store and access the data, with the CDO <a href="https://www.techtarget.com/searchcio/reference/CIO-job-description-Chief-information-officer-responsibilities">working collaboratively with the CIO</a> on the technologies to ensure support of the enterprise's objectives around data use, governance and monetization.</p> </section> <section class="section main-article-chapter" data-menu-title="Salary of the CDO"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Salary of the CDO</h2> <p>The average compensation of a CDO in the U.S. can vary widely, depending on the responsibilities associated with the CDO's diverse, expanding and evolving role. According to Payscale, CDO compensation in 2025 ranges from just over $100K up to about $280K, based on experience and type of business. A typical compensation package includes the base salary, plus bonuses and profit sharing. The median is about $175K.</p> </section> <section class="section main-article-chapter" data-menu-title="Career path and tenure info"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Career path and tenure info</h2> <p>Research shows that CDOs come from a variety of prior positions in the enterprise, many with data-centric roles that involve business intelligence and analytics. Many have also been promoted to CDO after working in IT-related jobs, marketing positions and even finance posts. <a href="https://www.techtarget.com/searchbusinessanalytics/feature/Chief-data-officer-role-key-to-data-driven-decision-making">Today's CDO in data-driven companies</a> such as banks and investment firms typically possesses a master's degree in technology or an MBA, plus managerial or supervisory experience, and expertise in data collection, management, analysis and perhaps data science.</p> <p>The average <a target="_blank" href="https://hbr.org/2021/08/why-do-chief-data-officers-have-such-short-tenures" rel="noopener">tenure</a> for CDOs is less than three years. Turnover in the role is high due to a combination of factors:</p> <ul class="default-list"> <li>Unclear corporate priorities.</li> <li>Unrealistic corporate expectations.</li> <li>Organizational resistance to newer technologies.</li> <li>CDO's lack of executive experience.</li> <li>Difficulty undertaking cultural change.</li> <li>Struggle to <a href="https://www.techtarget.com/searchcio/tip/15-tips-for-delivering-a-successful-presentation-to-the-board">demonstrate value and achievements to business audiences</a>.</li> </ul> </section> <section class="section main-article-chapter" data-menu-title="Future of the CDO role"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Future of the CDO role</h2> <p>Organizations have been gathering and compiling data as long as they've existed. But the volume of data started to grow exponentially with the rise of computer systems in the second half of the 20th century. Meanwhile, organizations sought and increasingly found opportunities to analyze and monetize that growing body of data.</p> <p>The <a href="https://www.techtarget.com/searchdatamanagement/feature/10-chief-data-officer-trends-that-are-reshaping-the-role">CDO role has evolved</a> in response to increased <a href="https://www.techtarget.com/searchcio/definition/regulatory-compliance">compliance regulations</a> such as the EU General Data Protection Regulation (GDPR). A large part of the CDO's job has typically entailed helping an enterprise create data governance policies that support the organization's compliance requirements. The focus of the position has shifted to helping organizations understand that <a href="https://www.techtarget.com/searchdatamanagement/definition/big-data">big data</a> is a business asset that can be used strategically to drive innovation, identify new revenue opportunities, and reduce operating costs.</p> <p>Additional factors impacting the profession include the following:</p> <ul class="default-list"> <li><b>AI. </b>CDOs must be fluent in AI technology to take advantage of its benefits.</li> <li><b>Short tenure. </b>CDO jobs usually last about three years, making the role often a springboard to a higher position, such as a CIO or COO.</li> <li><b>ROI requirements. </b>Since one of the main goals for a CDO is to monetize available data effectively, there might be pressure to demonstrate quickly how data can translate into revenue, especially with senior management, investors and other stakeholders</li> <li><b>Role overlap. </b>The chief data and analytics officer (CDAO) role might be a next step for an existing CDO; it might also indicate that CDOs need to grow their expertise in data analytics</li> <li><b>Strategic focus. </b>Like other senior leaders, CDOs must translate what they do into what board members will understand, especially when demonstrating how their initiatives impact profits and business value</li> <li><b>A data-driven culture. </b>This is no longer a classroom discussion point; it is essential for business success.</li> </ul> <p>As more organizations digitally transform and move to a data-driven decision management (<a href="https://www.techtarget.com/whatis/definition/data-driven-decision-management-DDDM">DDDM</a>) strategy, the CDO must ensure that business users have easy access to relevant data and reporting tools and can trust the <a href="https://www.techtarget.com/searchdatamanagement/definition/data-quality">data's quality</a>. To that end, the <a target="_blank" href="https://iscdo.org/" rel="noopener">International Society of Chief Data Officers</a>, a vendor-neutral peer-advisory resource affiliated with the Massachusetts Institute of Technology, helps members "strive to enable their enterprises to derive the maximum value from its <a href="https://www.techtarget.com/whatis/definition/information-assets">information and data assets</a>, to realize the value of data-driven decision-making and to gain competitive advantage through high-quality information."</p> <p>CDOs today are increasingly being recognized as integral to data-driven companies that are monetizing their data to improve business operations, product development, manufacturing, marketing campaigns, employee engagement and <a href="https://www.techtarget.com/whatis/feature/Top-customer-experience-conferences-to-attend">customer experiences</a>. But there's a long way to go.</p> <p>Many companies are in various stages of digitally transforming or have yet to embark on the journey. One-fourth of organizations reported being at the maturity level of implementing and optimizing several <a href="https://research.esg-global.com/chapters/ApplicationInfrastructureModernizationTrendsReport/ResearchFindings">digital transformation initiatives</a>, while nearly three-fourths are in process, just beginning or only planning to digitally transform, according to Omdia, a division of Informa TechTarget.</p> <p>As more organizations <a href="https://www.techtarget.com/searchitchannel/feature/Digital-transformation-in-manufacturing-melds-emerging-tech">accelerate their digital transformation initiatives</a> to continue competing at a high level, the evolving role and title of the CDO should achieve greater clarity, importance and C-level acceptance beyond the core responsibilities of creating a data usage strategy, managing the flow of data, breaking data silos and ensuring <a href="https://www.techtarget.com/searchdatamanagement/definition/compliance">compliance</a> with regulations. Future CDOs will ideally possess a combination of data management, AI and analytics skills, executive experience and the ability to measure value in business terms.</p> </section> A chief data officer (CDO) in many organizations is a C-level executive whose position has evolved into a range of strategic data management responsibilities, including data governance, data quality and data strategy. https://cdn.ttgtmedia.com/visuals/digdeeper/5.jpg https://www.techtarget.com/searchcio/definition/chief-data-officer-CDO Fri, 31 Oct 2025 11:48:00 GMT What is a chief data officer (CDO)? <p>Counterintelligence (CI) is the information gathered and actions taken to identify and protect against an adversary's knowledge collection activities or attempts to cause harm through sabotage or other actions. Cyber counterintelligence (CCI) is an emerging field that focuses on the active gathering of information about electronic <a href="https://www.techtarget.com/whatis/definition/threat-actor">threat actors</a>, their methods and techniques, and responding to these threats.</p> <section class="section main-article-chapter" data-menu-title="What is cyber counterintelligence?"> <h2 class="section-title"><i class="icon" data-icon="1"></i>What is cyber counterintelligence?</h2> <p>Cyber counterintelligence is the combination of traditional counterintelligence principles and modern <a href="https://www.techtarget.com/searchsecurity/definition/cybersecurity">cybersecurity</a> practices.</p> <h3>Counterintelligence</h3> <p>In the U.S., the National Institute of Standards and Technology (<a href="https://www.techtarget.com/searchsoftwarequality/definition/NIST">NIST</a>) defines counterintelligence as: "Information gathered and activities conducted to identify, deceive, exploit, disrupt, or protect against espionage, other intelligence activities, sabotage, or assassinations conducted for or on behalf of foreign powers, organizations, or persons, or their agents, or international terrorist organizations or activities."</p> <p>CI is often associated with intelligence agencies, government organizations or the military, but businesses also benefit from including CI in their <a href="https://www.techtarget.com/healthtechsecurity/feature/Understanding-NISTs-post-quantum-cryptography-standards">approach to security</a>. The principles of CI have been established over countless years of adversarial relations between competing parties. The fundamental truth that "knowledge is power" is at its core. By gaining knowledge of an adversary through research and espionage, the advantage of surprise can be eliminated. And advantage can be gained by limiting available information to an attacker or feeding them false information.</p> <h3>Cybersecurity</h3> <p>Cybersecurity is the <a href="https://www.techtarget.com/searchsecurity/feature/How-to-become-a-cybersecurity-architect">practice of securing digital assets</a>. It is a discipline of <a href="https://www.techtarget.com/searchsecurity/definition/What-is-risk-management-and-why-is-it-important">risk management</a>. Security controls are enforced to protect information. This is referred to as the information <i>security triad of</i> <i>confidentiality, availability and integrity</i> (<a href="https://www.techtarget.com/whatis/definition/Confidentiality-integrity-and-availability-CIA">CIA triad</a>).</p> <p>The <a href="https://www.techtarget.com/searchsecurity/definition/NIST-Cybersecurity-Framework">NIST Cybersecurity Framework</a> is a published standard of best practices. It has five main functions: identify, protect, detect, respond and recover.</p> <figure class="main-article-image full-col" data-img-fullsize="https://www.techtarget.com/rms/onlineimages/tips_to_reduce_attack_surfaces-f.png"> <img data-src="https://www.techtarget.com/rms/onlineimages/tips_to_reduce_attack_surfaces-f_mobile.png" class="lazy" data-srcset="https://www.techtarget.com/rms/onlineimages/tips_to_reduce_attack_surfaces-f_mobile.png 960w,https://www.techtarget.com/rms/onlineimages/tips_to_reduce_attack_surfaces-f.png 1280w" alt="Graphic of tips to reduce attack surfaces." height="269" width="560"> <figcaption> <i class="icon pictures" data-icon="z"></i>To secure digital assets, reduce attack surfaces. </figcaption> <div class="main-article-image-enlarge"> <i class="icon" data-icon="w"></i> </div> </figure> <h3>Cyber counterintelligence</h3> <p>Cyber counterintelligence combines the two fields of counterintelligence and cybersecurity. It recognizes that in the cyber domain, an attacker can have a greater advantage over the defender and seeks to equalize the playing field through the defender taking a more active role by applying counterintelligence principles. The intent isn't to try to stop attacks or mitigate risk, rather the goal is to try to stop adversaries from gaining <a href="https://www.techtarget.com/whatis/definition/threat-intelligence-cyber-threat-intelligence">intelligence</a>.</p> <p>CCI, therefore, differs from traditional cybersecurity in that it takes an <a href="https://www.techtarget.com/searchsecurity/feature/How-AI-threat-detection-is-transforming-enterprise-cybersecurity">active role in finding threats</a> instead of a simple passive, defensive role. To illustrate this difference, most traditional cybersecurity is defensive. If a network was a castle, that means strengthening the walls, locking doors and posting guards. Counterintelligence on the other hand is more active; it would be sending out spies and laying traps for threat actors.</p> <p>Many organizations practice aspects of CI, but refer to it by different names, including data loss prevention (<a href="https://www.techtarget.com/whatis/definition/data-loss-prevention-DLP">DLP</a>), malware reverse engineering and network forensics. Government agencies and cybersecurity firms do focused investigations into advanced persistent threat (<a href="https://www.techtarget.com/searchsecurity/definition/advanced-persistent-threat-APT">APT</a>) groups. As more important systems and networks become interconnected, cyberespionage becomes a bigger threat to nations.</p> <figure class="main-article-image full-col" data-img-fullsize="https://www.techtarget.com/rms/onlineimages/stages_of_an_advanced_persistent_threat-f.png"> <img data-src="https://www.techtarget.com/rms/onlineimages/stages_of_an_advanced_persistent_threat-f_mobile.png" class="lazy" data-srcset="https://www.techtarget.com/rms/onlineimages/stages_of_an_advanced_persistent_threat-f_mobile.png 960w,https://www.techtarget.com/rms/onlineimages/stages_of_an_advanced_persistent_threat-f.png 1280w" alt="Graphic of the stages of an advanced persistent threat." height="495" width="560"> <figcaption> <i class="icon pictures" data-icon="z"></i>The eight stages of an advanced persistent threat. </figcaption> <div class="main-article-image-enlarge"> <i class="icon" data-icon="w"></i> </div> </figure> </section> <section class="section main-article-chapter" data-menu-title="How counterintelligence works"> <h2 class="section-title"><i class="icon" data-icon="1"></i>How counterintelligence works</h2> <p>Counterintelligence activities can be categorized as being either collective, defensive or offensive.</p> <p><i>Collective CI</i><b> </b>efforts focus on collecting information about the adversary. It includes learning who the adversary is, how they collect information, what <a href="https://www.techtarget.com/searchsecurity/definition/attack-vector">attack vectors</a> they are targeting and what tools they are using. The <a href="https://www.techtarget.com/searchsecurity/definition/MITRE-ATTCK-framework">Mitre ATT&CK framework</a> is an open repository of knowledge about attackers and their methods. It is one of the primary sources of collected attacker information.</p> <p><i>Defensive CI</i> efforts focus on securing information and preventing an adversary from stealing or destroying it. It overlaps with traditional cybersecurity but differs in that it takes an assumed breach posture. In proactive <a href="https://www.techtarget.com/searchsecurity/tip/Threat-intelligence-vs-threat-hunting-Better-together">threat hunting</a>, security teams actively look for <a href="https://www.techtarget.com/searchsecurity/definition/Indicators-of-Compromise-IOC">indicators of compromise</a> in systems to try and detect attackers who have already bypassed defensive measures. <a href="https://www.darkreading.com/cyber-risk/how-to-get-the-most-out-of-ueba">User and entity behavior analytics</a> uses heuristics to try and find malicious activity hidden in normal seeming activity.</p> <p><i>Offensive CI</i> activities focus on turning an attack into an opportunity to gain an advantage by using disinformation. <a href="https://www.techtarget.com/searchsecurity/definition/honey-pot">Honeypots</a> are attractive looking targets for attackers intentionally left for them to find. Their use has expanded into entire honeynets and honeytokens that can distract an attacker and alert when accessed.</p> <div class="youtube-iframe-container"> <iframe id="ytplayer-0" src="https://www.youtube.com/embed/QwRnGJdXGaA?si=Pf84r9t_1FjdRY__?autoplay=0&modestbranding=1&rel=0&widget_referrer=null&enablejsapi=1&origin=https://www.techtarget.com" type="text/html" height="360" width="640" frameborder="0" loading="lazy"></iframe> </div> <p>While most information technology (IT) security administrators routinely conduct defensive CI and collective CI, the value of using offensive CI is not always understood. With the right implementation, <a href="https://www.techtarget.com/whatis/definition/deception-technology">deception technology</a> can be used to improve collective, defensive and offensive CI.</p> <p>Deception technology uses decoys, such as <a href="https://www.techtarget.com/searchsecurity/tip/How-honey-tokens-support-cyber-deception-strategies">honeypots and virtual honeypots</a>, to misdirect an attack and delay or prevent the attacker from going deeper into the network and reaching the intended target. By observing the tactics, techniques and procedures attackers use, defenders can gain valuable insight that can be incorporated into their defenses.</p> </section> Counterintelligence (CI) is the information gathered and actions taken to identify and protect against an adversary's knowledge collection activities or attempts to cause harm through sabotage or other actions. https://cdn.ttgtmedia.com/visuals/digdeeper/3.jpg https://www.techtarget.com/whatis/definition/counterintelligence Fri, 31 Oct 2025 00:00:00 GMT What is counterintelligence? <p>Natural language processing (NLP) is the ability of a computer program to understand human language as it's spoken and written -- referred to as natural language. It's a component of <a href="https://www.techtarget.com/searchenterpriseai/definition/AI-Artificial-Intelligence">AI</a>.</p> <p>Computers with NLP capabilities can not only recognize and understand natural human language, but also communicate with humans in the same language. These capabilities allow the machines to understand and respond to human commands, find information, answer questions, generate text, translate text, and more.</p> <p>NLP, which has roots in linguistics, has existed for more than 50 years and has various real-world applications in numerous fields, including <a href="https://www.techtarget.com/healthtechanalytics/answer/AI-Based-Natural-Language-Processing-Advances-Precision-Medicine">medical research</a>, search engines and business intelligence.</p> <div class="youtube-iframe-container"> <iframe id="ytplayer-0" src="https://www.youtube.com/embed/tUT9PD5ttMo?si=lYuMsmIsBic9Oczl?autoplay=0&modestbranding=1&rel=0&widget_referrer=null&enablejsapi=1&origin=https://www.techtarget.com" type="text/html" height="360" width="640" frameborder="0" loading="lazy"></iframe> </div> <p>NLP uses either <a href="https://www.techtarget.com/searchenterpriseai/feature/How-to-choose-between-a-rules-based-vs-machine-learning-system">rule-based or machine learning</a> approaches to understand the structure and meaning of text. Machine learning and NLP play a role in <a href="https://www.techtarget.com/searchcustomerexperience/definition/chatbot">chatbots</a>, voice assistants, text-based scanning programs, translation applications and enterprise software that aids in business operations, increases productivity and simplifies different processes.</p> <section class="section main-article-chapter" data-menu-title="Why is natural language processing important?"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Why is natural language processing important?</h2> <p>Businesses use large amounts of <a href="https://www.techtarget.com/searchbusinessanalytics/definition/unstructured-data">unstructured</a>, text-heavy data and need a way to efficiently process it. Much of the information created online and stored in databases is natural human language, and until recently, businesses couldn't effectively analyze this data. This is where natural language processing is useful.</p> <p>NLP enables computers to recognize and understand the text stored in human language. It also generates text in natural language, allowing human users to draw useful insights and inferences from the data to help them optimize real-world decisions and actions.</p> <p>The ability of NLP-enabled computers to quickly and accurately process vast quantities of unstructured text is one reason why the NLP market size is growing. According to <a target="_blank" href="https://www.statista.com/outlook/tmo/artificial-intelligence/natural-language-processing/worldwide" rel="noopener">Statista</a>, the NLP market is projected to reach a value of $53.42 billion in 2025. It is also expected to continue to grow at a CAGR of 24.76% (2025-2031). By 2031, the market volume is projected to hit $201.49 billion.</p> <p>The advantages of natural language processing can be seen when considering the following two statements: "Cloud computing insurance should be part of every service-level agreement" and "A good SLA ensures an easier night's sleep -- even in the cloud." If a user relies on natural language processing for search, the program will recognize that <i>cloud computing</i> is an entity, that <i>cloud</i> is an abbreviated form of cloud computing, and that <i><a href="https://www.techtarget.com/searchitchannel/definition/service-level-agreement">SLA</a></i> is an industry acronym for service-level agreement.</p> <p>These are the types of vague elements that frequently appear in human language and that <a href="https://www.techtarget.com/whatis/definition/machine-learning-algorithm">machine learning algorithms</a> have historically been bad at interpreting. Now, with improvements in <a href="https://www.techtarget.com/searchenterpriseai/definition/deep-learning-deep-neural-network">deep learning</a> and <a href="https://www.techtarget.com/searchenterpriseai/definition/machine-learning-ML">machine learning</a> methods, algorithms can effectively interpret them. These improvements expand the breadth and depth of data that can be analyzed, allowing employees to save time. NLP-enabled automation also reduces the potential for errors -- a common problem with manual, human-dependent document analysis and interpretation.</p> <p>Likewise, NLP has furthered developments into generative AI (<a href="https://www.techtarget.com/searchenterpriseai/definition/generative-AI">GenAI</a>). When a person interacts with a GenAI chatbot or an AI voice assistant like Siri on their phone, they don't need to use a specific predefined language or complex technical jargon. Instead, they could interact with the chatbot or voice assistant using their regular diction and simple, familiar language. The voice assistant will still be able to understand them and respond to their queries in similarly natural, human-understandable language.</p> <figure class="main-article-image half-col" data-img-fullsize="https://www.techtarget.com/rms/onlineimages/enterprise_ai-natural_language_processing-h.png"> <img data-src="https://www.techtarget.com/rms/onlineimages/enterprise_ai-natural_language_processing-h_half_column_mobile.png" class="lazy" data-srcset="https://www.techtarget.com/rms/onlineimages/enterprise_ai-natural_language_processing-h_half_column_mobile.png 960w,https://www.techtarget.com/rms/onlineimages/enterprise_ai-natural_language_processing-h.png 1280w" alt="Info box outlining the uses of natural language processing." height="176" width="279"> <figcaption> <i class="icon pictures" data-icon="z"></i>These are some of the key areas in which a business can use NLP. </figcaption> <div class="main-article-image-enlarge"> <i class="icon" data-icon="w"></i> </div> </figure> <p>Many enterprise software solutions also incorporate NLP capabilities. These solutions can recognize, analyze and generate text in human language to support various <a href="https://www.techtarget.com/searchcio/definition/business-process">business processes</a> and activities. For example, organizations can use NLP-enabled tools to do the following:</p> <ul class="default-list"> <li>Automate some business <a href="https://www.techtarget.com/searchcontentmanagement/definition/workflow-automation">workflows</a> that previously relied exclusively on human labor, in order to save time, streamline processes and increase employee productivity.</li> <li>Analyze customer call transcripts and chat logs to gauge customer sentiment and ultimately improve customer support.</li> <li>Simplify HR processes around hiring, <a href="https://www.techtarget.com/searchhrsoftware/definition/employee-onboarding-and-offboarding">onboarding, offboarding</a> and training so HR personnel can focus on other strategic tasks.</li> <li>Analyze transaction patterns and communication data to identify suspicious transactions and potential fraud.</li> </ul> </section> <section class="section main-article-chapter" data-menu-title="Benefits of natural language processing"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Benefits of natural language processing</h2> <p>The main benefit of NLP is that it improves the way humans and computers communicate with each other. The most direct way to manipulate a computer is through <a href="https://www.techtarget.com/whatis/definition/code">code</a> -- the computer's language. Enabling computers to understand human language makes interacting with computers much more intuitive for humans, so they don't have to know or use programming languages. Instead, users can input commands, requests or questions in simple natural language and expect to get appropriate responses in the same language.</p> <p>By easing communication between humans and machines, NLP simplifies many tasks that would otherwise require a lot of time and effort. For example, it can help automate tasks like text translations, data entry and content summarization, as well as tasks related to <a href="https://www.itprotoday.com/ai-machine-learning/unlocking-the-power-of-ai-in-intelligent-document-processing">document processing</a> and customer support.</p> <p>NLP-enabled machines can also do the following:</p> <ul class="default-list"> <li>Extract useful data from forms and other documents.</li> <li>Analyze and process documents containing unstructured data, such as contracts, SLAs and social media posts.</li> <li>Classify and filter information from content.</li> <li>Display information in response to human commands (e.g., routes or weather).</li> </ul> <p>Some of the other benefits of NLP include the following:</p> <ul class="default-list"> <li>Improved accuracy and efficiency of documentation.</li> <li>Organizations can use chatbots for routine customer support queries, allowing human agents to focus on more complex issues.</li> <li>NLP can automatically make a readable summary of a larger, more complex original text, thus speeding up document processing and analysis.</li> <li>Organizations can perform unstructured data analysis while minimizing the need for human input and reducing the potential for errors and slowdowns.</li> <li>Personal assistants such as Alexa can understand the spoken word and respond to human commands.</li> <li>Customer care teams can better understand social media posts, surveys and reviews in order to perform customer <a href="https://www.techtarget.com/searchbusinessanalytics/definition/opinion-mining-sentiment-mining">sentiment analysis</a>.</li> <li>Organizations can use NLP to optimize <a target="_blank" href="https://www.forbes.com/sites/neilsahota/2024/01/17/the-ai-revolution-in-lead-generationnavigating-new-business-frontiers/?sh=6682eb3312ea" rel="noopener">lead generation</a> by automatically identifying high-intent prospects, qualifying leads and tailoring content to maximize the potential for conversion.</li> <li>NLP tools provide advanced insights from <a href="https://www.techtarget.com/searchbusinessanalytics/definition/big-data-analytics">analytics</a> that were previously unreachable because of the large size and variability (different types of data) of datasets.</li> </ul> </section> <section class="section main-article-chapter" data-menu-title="Challenges of natural language processing"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Challenges of natural language processing</h2> <p>There are numerous challenges in natural language processing, and most of them boil down to the fact that natural language is ever-evolving, somewhat ambiguous and hasn't yet been perfected. As a result, semantic analysis can still be a challenge, meaning the NLP system might struggle to understand the meaning and context of human language and to correctly interpret the user's underlying intent.</p> <p>Some of the key challenges with NLP include the following:</p> <ul class="default-list"> <li><b>Precision. </b>Computers traditionally require humans to <i>speak </i>to them in a programming language that's precise, unambiguous and highly structured -- or through a limited number of clearly enunciated voice commands. Human speech, however, isn't always precise; it's often ambiguous and the linguistic structure can depend on many <a href="https://www.techtarget.com/searchenterpriseai/feature/How-emotion-analytics-will-impact-the-future-of-NLP">complex variables</a>, including slang and idioms, regional dialects, mispronunciations, incorrect grammar and social context. These variations can result in the NLP misinterpreting or misunderstanding human inputs and generating incorrect outputs.</li> <li><b>Abstract language use.</b> The abstract use of language is typically tricky and complex for programs to understand. For instance, natural language processing doesn't easily pick up on sarcasm or understand human emotions like confusion or horror. To do so, the machine would need to understand the words being used and their context in a conversation -- something that they are not yet able to do.</li> <li><b>Different meanings of the same sentence.</b> In some cases, the meaning of a sentence can change completely, depending on which word or syllable the speaker puts stress on. For example, a sentence like "I didn't say I don't like her" can mean different things, depending on whether the first <i>I</i> or the word <i>say</i> are stressed. Stressing the first I: "<i>I</i> didn't say I don't like her" means that the user didn't say it but someone else did, while stressing <i>say</i>: "I didn't <i>say</i> I don't like her" could mean that the user only thought about disliking her but didn't actually say it. Machines cannot parse these subtle differences, again resulting in incorrect or unreliable semantic analysis and inaccurate output.</li> <li><b>Variations in voice, tone, inflection.</b> When performing <a href="https://www.techtarget.com/searchcustomerexperience/definition/speech-recognition">speech recognition</a>, NLP <a href="https://www.techtarget.com/whatis/definition/algorithm">algorithms</a> can miss the subtle but important tone changes in a person's voice that can completely change the meaning of a word or sentence. Consider a simple phrase like, "Excuse me." When said softly, it indicates the speaker's request for someone's attention or for space, but when said loudly, it could indicate the speaker's disgust, frustration, or anger with a person or situation. NLP cannot differentiate between the two tones so it can misinterpret the meaning.</li> <li><b>Accents.</b> The risk of language misinterpretation by NLP increases <a href="https://www.techtarget.com/whatis/feature/How-AI-speech-recognition-shows-bias-toward-different-accents">due to accents</a>. Many NLP models are trained on language data spoken in a specific accent (e.g., American) so when the system encounters a different accent in the real world, it might not be able to understand the user. The most common issue with accents is variations in pronunciation, tone and inflection of speech. These elements can be challenging for an NLP algorithm to parse.</li> <li><b>Evolving use of language.</b> Natural language processing is also challenged by the fact that language -- and the way people use it -- is continually changing. Although there are rules to language, none are written in stone, and they're subject to change over time. Hard computational rules that work now might become obsolete, as the characteristics of real-world language change over time. For example, new vocabulary is continually being added to almost every human language. If the NLP model is not regularly trained on new words, phrases, idioms, etc., it might not generate accurate or reliable output when faced with previously unseen new inputs.</li> <li><b>Bias.</b> Biased training data <a href="https://www.techtarget.com/searchenterpriseai/feature/6-ways-to-reduce-different-types-of-bias-in-machine-learning">introduces bias</a> into NLP systems. This bias can be gender-related, ethnicity-related, age-related, and so on. If the training data skews toward a specific gender, race or age group, the NLP model will only learn from that data and accordingly capture biased semantic relationships. This can result in the reinforcement of existing stereotypes. It could also unfairly advantage or disadvantage certain persons or groups, leading to discrimination. This is a known issue in law enforcement, healthcare and <a href="https://www.techtarget.com/searchhrsoftware/tip/AI-hiring-bias-Everything-you-need-to-know">hiring</a>, and can lead to poor organizational decision-making, result in financial penalties imposed by regulators, damage the organization's reputation and even lead to physical injury or death.</li> </ul> </section> <section class="section main-article-chapter" data-menu-title="What is natural language processing used for?"> <h2 class="section-title"><i class="icon" data-icon="1"></i>What is natural language processing used for?</h2> <p>Natural language processing algorithms leverage rule-based modeling of human language to recognize, interpret and generate natural language text. In doing so, they can perform numerous functions and tasks.</p> <p>Some of the main functions and NLP tasks that natural language processing algorithms perform include the following:</p> <ul class="default-list"> <li><b>Text classification.</b> This function assigns tags to texts to put them in categories. This can be useful for sentiment analysis, which helps the natural language processing algorithm determine the sentiment, or emotion, behind a text. For example, when brand A is mentioned in X number of texts, the algorithm can determine how many of those mentions were positive and how many were negative. It can also be useful for intent detection, which helps predict what the speaker or writer might do based on the text they're producing.</li> <li><b>Text extraction.</b> This function automatically summarizes text and finds important pieces of data. One example of this is keyword extraction, which pulls the most important words from the text, which can be useful for <a href="https://www.techtarget.com/whatis/definition/search-engine-optimization-SEO">search engine optimization</a>. Doing this with natural language processing requires some programming -- it isn't completely automated. However, there are plenty of simple keyword extraction tools that automate most of the process -- the user just sets parameters within the program. For example, a tool might pull out the most frequently used words in the text. Another example is entity recognition, which extracts the names of people, places and other entities from text.</li> <li><b>Machine translation.</b> In this process, a computer translates text from one language, such as English, to another language, such as French, without human intervention.</li> <li><b>Natural language generation.</b> This process uses natural language processing algorithms to analyze unstructured data and automatically produce content based on that data. One example of this is in language models like the third-generation Generative Pre-trained Transformer (<a href="https://www.techtarget.com/searchenterpriseai/definition/GPT-3">GPT-3</a>), which can analyze unstructured text and then generate believable articles based on that text.</li> </ul> <p>The functions listed above are used in a variety of real-world applications and industries. Some of the most popular applications of NLP include the following:</p> <ul class="default-list"> <li><b>Customer feedback analysis.</b> Tools using AI can analyze social media reviews and filter out comments and queries for a company.</li> <li><b>AI for customer experience.</b> Voice assistants on a <a href="https://www.techtarget.com/searchcustomerexperience/news/366622116/Where-AI-really-fits-into-digital-customer-experience-tech">customer service</a> phone line can use speech recognition to understand what the customer is saying, so that it can direct their call correctly.</li> <li><b>Automatic translation.</b> Tools such as Google Translate, Bing Translator and Translate Me can translate text, audio and documents into another language.</li> <li><b>Academic research and analysis.</b> Tools using AI can analyze huge amounts of academic material and research papers based on the <a href="https://www.techtarget.com/whatis/definition/metadata">metadata</a> of the text as well as the text itself.</li> <li><b>Analysis and categorization of healthcare records.</b> AI-based tools can use insights to predict and, ideally, prevent disease.</li> <li><b>Plagiarism detection.</b> Tools such as Copyleaks and Grammarly use AI technology to scan documents and detect text matches and plagiarism.</li> <li><b>Stock forecasting and insights into financial trading.</b> NLP tools and platforms can analyze market history and annual reports that contain comprehensive summaries of a company's financial performance.</li> <li><b>Talent recruitment in human resources. </b>Organizations can <a href="https://www.techtarget.com/searchhrsoftware/feature/Advantages-and-disadvantages-of-using-AI-in-HR">use AI-based tools to reduce hiring time</a> by automating the candidate sourcing and screening process.</li> <li><b>Automation of routine litigation. </b>AI-powered tools can do research, identify possible issues and summarize cases faster than human attorneys.</li> <li><b>Spam detection.</b> NLP-enabled tools can be used to classify text for language that's often used in spam or <a href="https://www.techtarget.com/searchsecurity/definition/phishing">phishing</a> attempts. For example, AI-enabled tools can detect bad grammar, misspelled names, urgent calls to action and threatening terms.</li> </ul> <p>NLP is increasingly employed in numerous industries and departments, including the following:</p> <ul class="default-list"> <li><b>Legal.</b> Legal cases almost always require lawyers and paralegals to sift through vast numbers of documents containing vast volumes of unstructured data. NLP tools can quickly process these documents at scale and streamline data analysis to assist legal professionals with complex tasks related to legal discovery, legal research, document drafting, contract analysis, due diligence and <a href="https://www.techtarget.com/searchsecurity/definition/What-is-risk-management-and-why-is-it-important">risk management</a>.</li> <li><b>HR. </b>HR personnel can use NLP to simplify effort-intensive tasks like candidate sourcing, resume screening, interview scheduling and employee sentiment analysis. The time saved can be used to accelerate hiring, improve candidate experiences and implement new initiatives to improve <a href="https://www.techtarget.com/searchhrsoftware/definition/employee-engagement">employee engagement</a> and workplace experiences.</li> <li><b>Operations. </b>NLP-enabled systems are useful for a wide range of operational tasks and workflows, including customer support, predictive maintenance, quality control, process automation and <a href="https://www.techtarget.com/searcherp/definition/supply-chain-management-SCM">supply chain management</a>. NLP can provide automated support, generate actionable insights, classify information and process documents -- all of which can help business managers increase operational efficiency, reduce costs and risk, and make better-informed decisions.</li> <li><b>Data analytics.</b> NLP can extract key insights from unstructured documents and large datasets to identify useful patterns and trends that may not be readily obvious through manual (i.e., human "by eye") analysis. Different kinds of organizations can use the insights generated by the NLP system to inform their processes and decisions.</li> <li><b>Healthcare.</b> NLP-based tools trained on the right types of data can analyze health records, discharge summaries, research papers and other kinds of medical documents to extract key information and make accurate summaries. These insights and summaries enable care providers to make better, data-informed diagnostic and <a href="https://www.techtarget.com/healthtechanalytics/answer/How-NorthShore-Uses-AI-NLP-to-Tackle-SDOH-in-the-Emergency-Department">other decisions</a>. Some NLP systems can aid in drug discovery and research; others can detect certain medical conditions in a patient and predict their future health outcomes; still others can automate administrative tasks like report generation, document management or transcription. NLP-powered chatbots can interact with patients in personalized, human-like ways, thus improving patient access to care and enhancing provider-patient engagement.</li> <li><b>Insurance.</b> NLP systems can automatically extract key information from insurance claims, helping to speed up claims processing and resolution and reduce errors. Some tools can perform risk assessment of individuals based on their personal information, health history, financial history and other parameters to enable insurers to set the right premium, terms and conditions for their policies.</li> </ul> </section> <section class="section main-article-chapter" data-menu-title="How does natural language processing work?"> <h2 class="section-title"><i class="icon" data-icon="1"></i>How does natural language processing work?</h2> <p>NLP uses many different techniques to enable computers to understand natural language as humans do. Whether the language is spoken or written, natural language processing can use AI to take real-world input, process it and make sense of it in a way a computer can understand. Just as humans have different sensors -- such as ears to hear and eyes to see -- computers have programs to read and microphones to collect audio. And just as humans have a brain to process that input, computers have a program to process their respective inputs. At some point in processing, the input is converted to code that the computer can understand.</p> <p>There are four main phases to natural language processing: <a href="https://www.techtarget.com/searchdatamanagement/definition/data-preprocessing">data preprocessing</a>, feature extraction, algorithm development and model training.</p> <h3>Data preprocessing</h3> <p>Data preprocessing involves preparing and <i><a href="https://www.techtarget.com/searchdatamanagement/definition/data-scrubbing">cleaning text data</a> </i>so that machines can analyze it. Preprocessing puts data in a workable form and highlights features in the text that an algorithm can work with. There are several ways this can be done, including the following:</p> <ul class="default-list"> <li><b>Tokenization.</b> <a href="https://www.techtarget.com/searchsecurity/definition/tokenization">Tokenization</a> substitutes sensitive information with nonsensitive information, or a token. Tokenization is often used in payment transactions to protect credit card data.</li> <li><b>Stop word removal.</b> Common words are removed from the text, so unique words that offer the most information about the text remain.</li> <li><b>Lemmatization and stemming. </b><a href="https://www.techtarget.com/searchenterpriseai/definition/lemmatization">Lemmatization</a> groups together different inflected versions of the same word. For example, the word "walking" would be reduced to its root form, or stem, "walk" to process.</li> <li><b>Part-of-speech tagging.</b> Words are tagged based on which part of speech they correspond to -- such as nouns, verbs or adjectives.</li> </ul> <h3>Feature extraction</h3> <p>Feature extraction is the process of converting raw text -- which has already been cleaned and standardized -- into structured numerical representations using techniques like bag of words (<a href="https://www.techtarget.com/searchenterpriseai/tip/How-does-the-bag-of-words-model-work-in-NLP">BoW</a>), word embeddings or TF-IDF. The goal of such conversions is to ensure that a machine can analyze and interpret the text provided to it as input.</p> <p>Once the text is converted into a simpler, machine-readable form, the machine can identify patterns from the text, highlight key information within it and make predictions. Feature extraction accelerates NLP model training and improves model performance and output.</p> <h3>Algorithm development</h3> <p>Once the data has been preprocessed, an algorithm is developed to process it. There are many different natural language processing algorithms, but the following two main types are commonly used:</p> <ul class="default-list"> <li><b>Rule-based system.</b> This system uses carefully designed linguistic rules. This approach was used early in the development of natural language processing and is still used.</li> <li><b>Machine learning-based system.</b> Machine learning algorithms use statistical methods. They learn to perform tasks based on training data they're fed and adjust their methods as more data is processed. Using a combination of machine learning, deep learning and <a href="https://www.techtarget.com/searchenterpriseai/definition/neural-network">neural networks</a>, natural language processing algorithms hone their own rules through repeated processing and learning.</li> </ul> <h3>Model training</h3> <p>After the algorithm is selected, the model is <i>trained</i> on the processed data. Ideally, the training data should closely resemble real-world problems. This enables the model to identify patterns and learn correlations within the data, which will then allow it to produce more accurate output on <i>new</i> data.</p> <p>Organizations can use many data sources to train their NLP models. Reputable open source datasets and libraries are available for model training, although there's also the option to generate <a href="https://www.techtarget.com/searchcio/definition/synthetic-data">synthetic data</a> to improve the model and mitigate bias. Once a model is trained, it's important to continually fine-tune it. This helps to enhance its accuracy and relevance for real-world NLP tasks.</p> </section> <section class="section main-article-chapter" data-menu-title="Techniques and methods of natural language processing"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Techniques and methods of natural language processing</h2> <p>Syntax and semantic analysis are two main techniques used in natural language processing.</p> <h3>Syntax NLP techniques</h3> <p><i>Syntax</i> is the arrangement of words in a sentence to make grammatical sense. <a href="https://www.theserverside.com/tutorial/Natural-language-programming-using-GPTScript">NLP uses syntax</a> to assess meaning from a language based on grammatical rules. Syntax NLP techniques include the following:</p> <ul class="default-list"> <li><strong>Parsing.</strong> This is the grammatical analysis of a sentence. For example, a natural language processing algorithm is fed the sentence, "The dog barked." <a href="https://www.techtarget.com/searchapparchitecture/definition/parser">Parsing</a> involves breaking this sentence into parts of speech -- i.e., dog is a noun; barked is a verb. This is useful for more complex downstream processing tasks.<br>NLP algorithms can perform either dependency parsing or constituency parsing. The above sentence is an example of dependency parsing where the model looks at the relationships between words to differentiate between various parts of speech. Constituency parsing involves building a syntax tree that properly represents the syntactic structure of a sentence to make it understandable to the NLP model and to end users.</li> <li><strong>Word segmentation. </strong>Also known as tokenization, word segmentation is the act of taking a string of text and deriving word forms from it. For example, a person scans a handwritten document into a computer. The algorithm can analyze the page and recognize that the words are divided by white spaces.<br>Tokenization results in a word index that maps each unique word to a specific numerical identifier as well as tokenized text in which each word in the text is replaced by its corresponding numerical token. These elements are important for many NLP tasks, including translations and part-of-speech tagging.</li> <li><strong>Sentence breaking.</strong> This places sentence boundaries in large texts. For example, a natural language processing algorithm is fed the text, "The dog barked. I woke up." The algorithm can use sentence breaking to recognize the period that splits up the sentences. Various <a href="https://www.techtarget.com/searchenterpriseai/tip/Popular-libraries-to-use-for-machine-learning-projects">NLP libraries</a>, predefined rules or pretrained models are used to identify individual sentences from a body of text and make them available for useful NLP tasks like content summarization.</li> <li><strong>Morphological segmentation.</strong> This divides words into smaller meaningful parts called morphemes. For example, the word <i>untestable</i> would be broken into [[un[[test]able]], where the algorithm recognizes "un," "test," and "able" as morphemes. This is especially useful in named entity recognition (<a href="https://www.techtarget.com/whatis/definition/named-entity-recognition-NER">NER</a>), machine translation and speech recognition. Various methods of morphological segmentation are available, including surface segmentation and canonical segmentation.</li> <li><strong>Stemming.</strong> It divides words with inflections in them into root forms. This improves text processing and analysis. For example, in the sentence, "The dog barked," the algorithm would recognize the root of the word "barked" is "bark." This is useful if a user is analyzing text for all instances of the word bark, as well as all its conjugations. The algorithm can see that they're essentially the same word even though the letters are different.</li> </ul> <h3>Semantic NLP techniques</h3> <p><i>Semantics</i> involves the use of and meaning behind words. Natural language processing applies algorithms to understand the meaning and structure of sentences. <a href="https://www.techtarget.com/searchbusinessanalytics/feature/Agents-semantic-layers-among-top-data-analytics-trends">Semantic techniques</a> include the following:</p> <ul class="default-list"> <li><b>Word sense disambiguation</b><b>. </b>This derives the meaning of a word based on context. The same words might be used in different contexts and the NLP model should be able to identify the differences to demonstrate that it can accurately understand the text. <p>For example, consider the sentence, "The pig is in the pen." Here, the word <i>pen</i> has different meanings, depending on whether it refers to a writing implement or a place to house pigs. An NLP algorithm using this method can understand that the use of the word here refers to a fenced-in area for pigs, not a writing instrument.</p> </li> <li><b>Named entity recognition.</b> NER determines useful words or phrases -- generally known as "entities" -- that can be categorized into various groups. For example, an algorithm using this method could analyze a news article and identify all mentions of a certain company or product. Using the semantics of the text, it could differentiate between different entities that are represented by the same word. For instance, in the sentence, "Daniel McDonald's son went to McDonald's and ordered a Happy Meal," the algorithm could recognize the two instances of "McDonald's" as two separate entities -- one a restaurant and one a person.</li> <li><b>Natural language generation.</b> <a href="https://www.techtarget.com/searchenterpriseai/definition/natural-language-generation-NLG">NLG</a> uses a database to determine the semantics behind words and generate new text. For example, an algorithm could automatically write a summary of findings from a business intelligence (<a href="https://www.techtarget.com/searchbusinessanalytics/definition/business-intelligence-BI">BI</a>) platform, mapping certain words and phrases to features of the data in the BI platform. Another example would be automatically generating news articles or tweets based on a certain body of text used for training.<br>NLG is most commonly used to generate the auto-responses of chatbots and virtual assistants. It is also employed to automate emails, personalize responses to emails, generate customer support scripts, summarize news reports and create product descriptions for <a href="https://www.techtarget.com/searchcio/definition/e-commerce">e-commerce</a>.</li> </ul> </section> <section class="section main-article-chapter" data-menu-title="Natural language processing and deep learning"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Natural language processing and deep learning</h2> <p>Current approaches to natural language processing are based on deep learning, a type of AI that examines and uses patterns in data to improve a program's understanding. Deep learning models require massive amounts of labeled data for the natural language processing algorithm to train on and identify relevant correlations, and assembling this kind of <a href="https://www.techtarget.com/searchdatamanagement/definition/big-data">big data</a> set is one of the main hurdles to natural language processing.</p> <p>Earlier approaches to natural language processing involved a more rule-based approach, where simpler machine learning algorithms were told what words and phrases to look for in text and given specific responses when those phrases appeared. But deep learning is a more flexible, intuitive approach in which algorithms learn to identify speakers' intent from many examples -- almost like how a child would learn human language.</p> </section> <section class="section main-article-chapter" data-menu-title="NLP tools"> <h2 class="section-title"><i class="icon" data-icon="1"></i>NLP tools<a href="https://www.techtarget.com/whatis/definition/open-source"></a></h2> <p>Three <a href="https://www.techtarget.com/whatis/definition/open-source">open source</a> tools commonly used for natural language processing include Natural Language Toolkit (NLTK), Gensim, and NLP Architect by Intel AI Lab.</p> <ul class="default-list"> <li><b>NLTK. </b>This is a <a href="https://www.techtarget.com/whatis/definition/Python">Python</a> module with data sets and tutorials. It enables users to build Python programs that can work with natural language data. With NLTK, users can identify named entities, tokenize and tag text, and display parse trees. The platform also provides text processing libraries for stemming, parsing and semantic reasoning.</li> <li><b>Gensim.</b> This is a Python library for topic modeling and document indexing. It features intuitive interfaces and can be extended with other Vector Space algorithms. The Python packages NumPy and Scipy are required to install and use Gensim.</li> <li><b>NLP Architect</b> <b>by Intel AI Lab.</b> This is an open source Python library for deep learning topologies and techniques. It provides numerous core NLP models that can be used for many NLP tasks and applications. At the same time, it is flexible so new neural network components and data handling methods can be added to train and run new models.</li> </ul> </section> <section class="section main-article-chapter" data-menu-title="The evolution of natural language processing"> <h2 class="section-title"><i class="icon" data-icon="1"></i>The evolution of natural language processing</h2> <p>NLP draws from a variety of disciplines, including computer science and <a href="https://www.techtarget.com/searchenterpriseai/definition/computational-linguistics-CL">computational linguistics</a> developments dating back to the mid-20th century. Its evolution included the following major milestones:</p> <h3>1950s</h3> <p>Natural language processing has its roots in this decade, when Alan Turing developed the <a href="https://www.techtarget.com/searchenterpriseai/definition/Turing-test">Turing Test</a> to determine whether or not a computer is truly intelligent. The test involves automated interpretation and the generation of natural language as a criterion of intelligence.</p> <h3>1950s-1990s</h3> <p>NLP was largely rules-based, using handcrafted rules developed by linguists to determine how computers would process language. The Georgetown-IBM experiment in 1954 became a notable demonstration of machine translation, automatically translating more than 60 sentences from Russian to English. The 1980s and 1990s saw the development of rule-based parsing, morphology, semantics and other forms of natural language understanding.</p> <h3>1990s</h3> <p>The top-down, language-first approach to natural language processing was replaced with a more statistical approach because advancements in computing made this a more efficient way of developing NLP technology. Computers were becoming faster and could be used to develop rules based on linguistic statistics without a linguist creating all the rules. Data-driven natural language processing became mainstream during this decade. Natural language processing shifted from a linguist-based approach to an engineer-based approach, drawing on a wider variety of scientific disciplines instead of delving into linguistics.</p> <h3>2000-2020s</h3> <p>Natural language processing saw dramatic growth in popularity as a term. NLP processes using unsupervised and semisupervised machine learning algorithms were also explored. With advances in computing power, natural language processing has also gained numerous real-world applications. NLP also began powering other applications like chatbots and virtual assistants. Today, approaches to NLP involve a combination of classical linguistics and statistical methods.</p> <h3>2020s-Present day</h3> <p>Developments in the NLP field accelerated after 2020. One of the most visible and high-profile developments is the launch of <a href="https://www.computerweekly.com/feature/ChatGPT-Everything-you-need-to-know">ChatGPT</a>, an advanced AI chatbot that uses a large language model (<a href="https://www.techtarget.com/whatis/definition/large-language-model-LLM">LLM</a>) to understand human inputs in natural language and then provide fast, contextually relevant responses -- also in natural language.</p> <p>ChatGPT first launched in November 2022, and it was based on the GPT-3.5 LLM. <a href="https://www.techtarget.com/searchenterpriseai/definition/OpenAI">OpenAI</a>, the company that built ChatGPT, released the next LLM iteration, GPT-4 with more advanced generative capabilities in 2023. The company launched GPT-5 in August 2025, the most advanced model that powers ChatGPT and according to the firm, is "<a target="_blank" href="https://openai.com/gpt-5/" rel="noopener">available to everyone</a>".</p> <p>Another important NLP development is the emergence of multimodal models. These models can take in and interpret user inputs in multiple modes, not just text. For example, CLIP by OpenAI can understand and process both images and text to provide better quality output and enhance user experiences with NLP.</p> <p>Alongside LLMs, small language models (<a href="https://www.techtarget.com/whatis/definition/small-language-model-SLM">SLMs</a>) are also emerging in the NLP landscape. SLMs are smaller and have fewer capabilities than LLMs. These models can be fine-tuned on domain-specific data sets for use in specialized applications like chatbots or to meet the information retrieval needs of specific industries.</p> <p>In recent years, research has scaled up into several NLP-related or NLP-adjacent areas, such as <a href="https://www.techtarget.com/whatis/tip/AI-bias-mitigation-playbook">bias mitigation</a>, AI ethics, and zero-shot learning. Additionally, researchers are developing techniques to efficiently train models to reduce computational requirements and increase model accessibility and performance. These developments are likely to contribute to further advancements in NLP and create more applications for the use of NLP in the real world.</p> <p>Natural language processing plays a vital part in technology and the way humans interact with it. Though it has its challenges, NLP is expected to become more accurate with more sophisticated models, more accessible and more relevant in numerous industries. NLP will continue to be an important part of both industry and everyday life.</p> <p><i>As natural language processing is making significant strides in new fields, it's becoming more important for developers to learn how it works. Learn how to develop your skills in </i><a href="https://www.techtarget.com/searchenterpriseai/feature/QA-How-to-start-learning-natural-language-processing"><i>creating NLP programs</i></a><i>.</i></p> </section> Natural language processing (NLP) is the ability of a computer program to understand human language as it's spoken and written -- referred to as natural language. https://cdn.ttgtmedia.com/visuals/digdeeper/1.jpg https://www.techtarget.com/searchenterpriseai/definition/natural-language-processing-NLP Tue, 28 Oct 2025 00:00:00 GMT What is natural language processing (NLP)? <p>Desktop as a Service (DaaS) is a cloud computing offering in which a third party hosts the back end of a virtual desktop infrastructure (<a href="https://www.techtarget.com/searchvirtualdesktop/definition/virtual-desktop-infrastructure-VDI">VDI</a>) deployment.</p> <p>DaaS allows authorized end users who have a reliable internet connection to connect to a <a href="https://www.techtarget.com/searchvirtualdesktop/definition/virtual-desktop">virtual desktop</a> in the cloud from almost any type of computing device. Essentially, the user's PC, <a href="https://www.techtarget.com/searchnetworking/definition/thin-client">thin client</a>, tablet or smartphone becomes an access point that can connect remotely to a virtual desktop hosted by the <a href="https://www.techtarget.com/searchitchannel/definition/cloud-service-provider-cloud-provider">cloud service provider</a>. End users typically access their virtual desktop(s) through a web browser or dedicated client application provided by the DaaS vendor.</p> <p>DaaS offerings are designed to provide authorized users with the same responsive performance, personalized settings and seamless access to applications and files as in-house VDI deployments. With DaaS, however, the desktop operating systems (<a href="https://www.techtarget.com/whatis/definition/operating-system-OS">OSes</a>) and apps run inside virtual machines (<a href="https://www.techtarget.com/searchitoperations/definition/virtual-machine-VM">VMs</a>) that are hosted on <a href="https://www.techtarget.com/whatis/definition/server">servers</a> managed by the cloud service provider.</p> <section class="section main-article-chapter" data-menu-title="How does desktop as a service work?"> <h2 class="section-title"><i class="icon" data-icon="1"></i>How does desktop as a service work?</h2> <p>DaaS can be purchased through a subscription model that bundles infrastructure, OS licensing and (sometimes) <a href="https://www.techtarget.com/searchenterprisedesktop/definition/desktop-management">desktop management</a> services. In most cases, DaaS runs on a multi-tenant architecture in the cloud. Each tenant (customer) is logically isolated so their data, applications and policies remain secure and separate. In business settings, users might need to use credentials that are tied to an identity and access management (<a href="https://www.techtarget.com/searchsecurity/definition/identity-access-management-IAM-system">IAM</a>) system like <a target="_blank" href="https://www.microsoft.com/en-us/security/business/identity-access/microsoft-entra-id" rel="noopener">Microsoft Entra ID</a> (formerly Azure Active Directory) in order to access their virtual desktop(s).</p> <p>On the back end, the DaaS environment consists of several interconnected components. The management layer, which can also be called the <i>control plane</i> or <i>connection broker</i>, is responsible for provisioning or assigning desktops, monitoring their use and enforcing <a href="https://www.techtarget.com/searchsecurity/feature/How-to-create-a-data-security-policy-with-template">security policies</a>. Virtual machines provide the actual desktop environments, and <a href="https://www.techtarget.com/searchstorage/tip/Comparing-4-decentralized-data-storage-offerings">cloud storage systems</a> retain user files, profiles and settings.</p> <p>As with on-premises VDI, cloud desktop services use a <a href="https://www.techtarget.com/searchenterprisedesktop/definition/Remote-Desktop-Protocol-RDP">remote desktop protocol</a> like Microsoft RDP, <a target="_blank" href="https://www.citrix.com/glossary/what-is-hdx.html" rel="noopener">Citrix HDX</a> or <a target="_blank" href="https://blogs.vmware.com/euc/2016/09/story-of-vmware-blast.html" rel="noopener">VMware Blast</a> to stream virtual desktops to <a href="https://www.techtarget.com/whatis/definition/endpoint-device">endpoint devices</a>. This type of protocol continually sends the visual output of the user's desktop to the user's device while also capturing the user's keyboard strokes, mouse clicks and touchscreen gestures.</p> </section> <section class="section main-article-chapter" data-menu-title="VDI vs. DaaS"> <h2 class="section-title"><i class="icon" data-icon="1"></i>VDI vs. DaaS</h2> <p>VDI and DaaS are often confused because both involve delivering virtual desktops to end users, but they're deployed and managed in very different ways.</p> <p>VDI <a href="https://www.techtarget.com/searchvirtualdesktop/definition/desktop-virtualization">desktop virtualization</a> deployments run in an organization's own <a href="https://www.techtarget.com/searchdatacenter/definition/data-center">data center</a> or on <a href="https://www.techtarget.com/searchcloudcomputing/tip/Top-public-cloud-providers-A-brief-comparison">public cloud</a> infrastructure and are self-managed by the organization's own information technology (IT) staff.</p> <div class="youtube-iframe-container"> <iframe id="ytplayer-0" src="https://www.youtube.com/embed/Nz9r3HxI8qI?si=Tq5FtHlXjv-k3M0w?autoplay=0&modestbranding=1&rel=0&widget_referrer=null&enablejsapi=1&origin=https://www.techtarget.com" type="text/html" height="360" width="640" frameborder="0" loading="lazy"></iframe> </div> <p>In contrast, desktop as a service (<a href="https://www.techtarget.com/searchvirtualdesktop/definition/desktop-as-a-service-DaaS">DaaS</a>) is VDI technology that's delivered as a managed cloud service. Desktop as a service provides many of the same advantages that virtual desktop infrastructure does without requiring a significant upfront investment in compute, storage and network infrastructure.</p> <figure class="main-article-image full-col" data-img-fullsize="https://www.techtarget.com/rms/onlineimages/virt_desktop-vdi_vs_daas-f.png"> <img data-src="https://www.techtarget.com/rms/onlineimages/virt_desktop-vdi_vs_daas-f_mobile.png" class="lazy" data-srcset="https://www.techtarget.com/rms/onlineimages/virt_desktop-vdi_vs_daas-f_mobile.png 960w,https://www.techtarget.com/rms/onlineimages/virt_desktop-vdi_vs_daas-f.png 1280w" alt="This image compares VDI and DaaS infrastructure, management and cost." height="247" width="560"> <figcaption> <i class="icon pictures" data-icon="z"></i>VDI is self-managed and typically runs in an organization's own data center, while DaaS is a managed cloud service that provides virtual desktops through a subscription model. </figcaption> <div class="main-article-image-enlarge"> <i class="icon" data-icon="w"></i> </div> </figure> <p>It should be noted that if an organization runs its own VDI deployment on public cloud infrastructure, it's still VDI, not DaaS. It only becomes DaaS if the cloud provider or a third-party managed service provider (<a href="https://www.techtarget.com/searchitchannel/definition/managed-service-provider">MSP</a>) is responsible for running the VDI infrastructure <a href="https://www.techtarget.com/searchitchannel/Guide-to-building-and-executing-an-MSP-business-model">as a managed service</a>.</p> </section> <section class="section main-article-chapter" data-menu-title="Use cases for desktop as a service"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Use cases for desktop as a service</h2> <p>Desktop as a service is widely used in scenarios where scalability and centralized management are important concerns. DaaS is particularly attractive for large enterprises, <a target="_blank" href="https://github.com/yanirs/established-remote" rel="noopener">remote-first companies</a> and organizations in industries that have high compliance and/or data security requirements. Popular use cases for DaaS include:</p> <ul class="default-list"> <li><b>Improving security. </b>When properly configured, DaaS can <a href="https://www.techtarget.com/searchsecurity/tip/Cybersecurity-risk-management-Best-practices-and-frameworks">help mitigate many of the security risks</a> associated with physical devices, including risks posed by lost or stolen laptops, malware infections or insecure <a href="https://www.techtarget.com/searchdatabackup/definition/removable-media">removable media</a>. Common DaaS security features include multifactor authentication (<a href="https://www.techtarget.com/searchsecurity/definition/multifactor-authentication-MFA">MFA</a>), encryption, conditional access policies and the ability to restrict data transfers to specific types of endpoints or storage media.</li> <li><b>Providing better business continuity.</b> Desktop as a service <a href="https://www.techtarget.com/searchdatabackup/tip/Use-backup-and-business-continuity-planning-to-protect-data">supports business continuity</a> by allowing users to log in from anywhere. If a local office or data center experiences a disaster, work can continue from another location that still has power and internet connectivity.</li> <li><b>Supporting shift work.</b> DaaS deployments allow multiple employees on different work shifts to securely share the same physical computing device. Essentially, the physical computing device becomes a wired or <a href="https://www.techtarget.com/searchmobilecomputing/definition/access-point">wireless access point</a> that allows the user to connect to a cloud-hosted virtual desktop.</li> <li><b>Supporting remote and hybrid work.</b> DaaS makes it easier and safer for remote and hybrid employees to use corporate desktops and apps on personal computing devices.</li> <li><b>Supporting contractors and seasonal workers.</b> DaaS allows organizations to quickly provision desktops for temporary workers without having to purchase new hardware or build out additional infrastructure.</li> <li><b>Facilitating compliance in regulated industries.</b> Healthcare, finance, government and legal organizations often use DaaS to manage sensitive data in the cloud. This deployment model helps organizations meet compliance regulations, such as the Health Insurance Portability and Accountability Act (<a href="https://www.techtarget.com/searchhealthit/definition/HIPAA">HIPAA</a>), the Payment Card Industry Data Security Standard (<a href="https://www.techtarget.com/searchsecurity/definition/PCI-DSS-Payment-Card-Industry-Data-Security-Standard">PCI-DSS</a>) and/or the General Data Protection Regulation (<a href="https://www.computerweekly.com/opinion/GDPRs-7th-anniversary-in-the-AI-age-privacy-legislation-is-still-relevant">GDPR</a>), while also reducing security risks on devices.</li> <li><b>Allowing Mac users to run Windows. </b>DaaS gives Mac users the ability to work in a Windows environment without needing to use dual boot, Boot Camp or local virtualization software.</li> <li><b>Reducing hardware costs.</b> Because DaaS runs in the cloud, end users can use older PCs or <a href="https://www.techtarget.com/searchvirtualdesktop/tip/Evaluating-tablets-as-thin-clients-in-the-enterprise">tablets as thin clients</a>. This can extend the hardware's lifecycle while also helping to keep an organization's capital expenditures (<a href="https://www.techtarget.com/whatis/definition/CAPEX-capital-expenditure">Capex</a>) line items as low as possible.</li> </ul> </section> <section class="section main-article-chapter" data-menu-title="Advantages and disadvantages of DaaS"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Advantages and disadvantages of DaaS</h2> <p>Like any technology, desktop as a service has both <a href="https://www.techtarget.com/searchvirtualdesktop/feature/What-are-the-pros-and-cons-of-DaaS">advantages and disadvantages</a>. For example, while DaaS reduces the need for organizations to buy and maintain additional hardware and infrastructure for each new remote employee, a positive user experience (UX) depends on whether the remote worker has a reliable internet connection and sufficient <a href="https://www.techtarget.com/searchnetworking/definition/bandwidth">bandwidth</a>.</p> <p>Here are some additional pros and cons of using desktop-as-a-service technology:</p> <h3>Advantages of DaaS</h3> <ul class="default-list"> <li>Cloud service providers make it easy to scale virtual desktop deployments up or down as needed.</li> <li>DaaS lets users work from a computing device of their choosing.</li> <li>DaaS subscriptions can help organizations shift desktop delivery from a Capex to an Opex expense.</li> <li>In some cases, DaaS can help reduce licensing costs per user by allowing an application to be installed once in the user's cloud desktop and accessed from any device the service-level agreement (SLA) permits.</li> <li>Administrators can quickly disconnect a compromised device from the service through the cloud management platform or the organization's IAM system.</li> <li>DaaS can help simplify <a href="https://www.techtarget.com/searchdisasterrecovery/feature/Disaster-recovery-glossary-Terms-to-know">disaster recovery</a> by consolidating user data in the cloud.</li> </ul> <h3>Disadvantages of DaaS</h3> <ul class="default-list"> <li>If the end user's internet connection is unreliable, they might experience lag, <a href="https://www.techtarget.com/searchunifiedcommunications/definition/jitter">jitter</a> or lose access to their desktop.</li> <li>Some application vendors impose restrictions on how their software can be used in virtualized environments.</li> <li>Microsoft licenses for virtualized environments can be complex, especially when third-party DaaS providers are involved.</li> <li>Persistent desktop services are generally more expensive than nonpersistent ones because they require more resources.</li> </ul> </section> <section class="section main-article-chapter" data-menu-title="Persistent vs. nonpersistent DaaS desktops"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Persistent vs. nonpersistent DaaS desktops</h2> <p>Many DaaS providers support both persistent and nonpersistent desktops so organizations can match the right desktop type to different user needs and workloads.</p> <p>A <i>persistent</i> desktop saves all changes the user makes during a session, and the next time the user logs in, they are sent the same VM with all their changes intact. Persistent desktops provide end users with a highly personalized experience, but they require additional <a href="https://www.techtarget.com/searchstorage/definition/cloud-storage">cloud storage</a>, which can add to the cost of a subscription.</p> <p>In contrast, a <i>nonpersistent</i> desktop gives the user a fresh instance of the base desktop image each time they log in. When the user logs out, the desktop is reset to its original state and any changes are discarded. Nonpersistent desktops are easier and cheaper to manage at scale because they <a href="https://www.techtarget.com/searchvirtualdesktop/tip/How-to-create-and-manage-Azure-Virtual-Desktop-golden-images">use a single golden image</a>. Once an update, software patch or configuration change has been made to the golden image, it will be applied to all future user sessions.</p> </section> <section class="section main-article-chapter" data-menu-title="DaaS providers"> <h2 class="section-title"><i class="icon" data-icon="1"></i>DaaS providers</h2> <p>Organizations need to do their homework before selecting a DaaS provider. Not all DaaS services offer the same pricing, performance, security or compliance features, so decision-makers need to ensure the vendor and subscription tier they choose meet both the users' and organization's needs.</p> <p>The comparison table below provides an overview of the different factors organizations should consider before they select a DaaS provider.</p> <table class="main-article-table"> <thead> <tr> <td> <p><span style="color: #ecf0f1;"><b>Vendor / Product</b></span></p> </td> <td> <p><span style="color: #ecf0f1;"><b>Hosting</b></span></p> </td> <td> <p><span style="color: #ecf0f1;"><b>Requirements </b></span></p> </td> <td> <p><span style="color: #ecf0f1;"><b>Licensing</b></span></p> </td> <td> <p><span style="color: #ecf0f1;"><b>Setup</b></span></p> </td> <td> <p><span style="color: #ecf0f1;"><b>Support</b></span></p> </td> </tr> </thead> <tbody> <tr> <td> <p><b>Amazon WorkSpaces</b></p> </td> <td> <p>AWS public cloud (multi-region)</p> </td> <td> <p>AWS account</p> </td> <td> <p>OS license bundled; BYOL for Microsoft apps possible; hourly or monthly subscription pricing</p> </td> <td> <p>Minimal setup, auto-provisioned via AWS console</p> </td> <td> <p>Standard AWS Support plans (Basic, Developer, Business, Enterprise) -- charged separately</p> </td> </tr> <tr> <td> <p><b>Azure Virtual Desktop (AVD)</b></p> </td> <td> <p>Microsoft Azure cloud</p> </td> <td> <p>Azure subscription; Microsoft 365 or Windows license; Azure AD integration</p> </td> <td> <p>Eligible Microsoft 365/Windows licenses cover internal users; external users require additional access pricing; Azure resources billed separately</p> </td> <td> <p>Moderate setup -- requires Azure infra and identity integration</p> </td> <td> <p>Microsoft Unified Support or pay-as-you-go Azure support tiers</p> </td> </tr> <tr> <td> <p><b>Omnissa Horizon Cloud</b> <i>(formerly VMware Horizon Cloud)</i></p> </td> <td> <p>Omnissa cloud + hybrid deployment options</p> </td> <td> <p>Horizon subscription; enterprise IT team for deployment</p> </td> <td> <p>Subscription-based; costs vary by package (Standard, Advanced, Enterprise); Microsoft licensing rules apply</p> </td> <td> <p>Higher setup effort; best for enterprises that need hybrid cloud services</p> </td> <td> <p>Omnissa enterprise support (successor to VMware Global Support Services)</p> </td> </tr> <tr> <td> <p><b>Dizzion Frame</b> <i>(formerly Nutanix Frame)</i></p> </td> <td> <p>Dizzion cloud or customer cloud (AWS, Azure, GCP)</p> </td> <td> <p>Dizzion subscription</p> </td> <td> <p>Licensing bundled with subscription; flexible hybrid deployment supported</p> </td> <td> <p>Low to moderate setup -- browser-based management simplifies provisioning</p> </td> <td> <p>Direct support from Dizzion (24/7 options available), often bundled into subscription</p> </td> </tr> <tr> <td> <p><b>Citrix DaaS</b> <i>(formerly Citrix Virtual Apps and Desktops Service)</i></p> </td> <td> <p>Citrix Cloud service on Azure, AWS, GCP, or hybrid</p> </td> <td> <p>Citrix Cloud subscription; enterprise identity system</p> </td> <td> <p>Subscription-based; integrates with Microsoft licensing for Windows; supports SaaS, VDI, and hybrid deployments</p> </td> <td> <p>Moderate to high setup depending on architecture; strong use in regulated industries</p> </td> <td> <p>Citrix Standard and Premium Support packages; enterprise SLAs available</p> </td> </tr> </tbody> </table> <p><i>Learn </i><i>more about Omnissa, the company that took over VMware's end-user computing division, and <a href="https://www.techtarget.com/searchvirtualdesktop/opinion/Who-owns-Omnissa-and-whats-next-for-this-vendor">find out what's expected next</a> for this vendor's subscription licensing model and product offerings.</i></p> </section> Desktop as a service (DaaS) is a cloud computing offering in which a third party hosts the back end of a virtual desktop infrastructure (VDI) deployment. https://cdn.ttgtmedia.com/visuals/digdeeper/6.jpg https://www.techtarget.com/searchvirtualdesktop/definition/desktop-as-a-service-DaaS Wed, 15 Oct 2025 00:00:00 GMT What is desktop as a service (DaaS)? <h3>What is a unified computing system (UCS)?</h3> <p>A unified computing system (UCS) is a <a href="https://www.techtarget.com/searchdatacenter/definition/converged-infrastructure">converged</a> data center architecture that integrates computing, networking and storage resources to increase efficiency and enable centralized management. Modern UCS solutions are AI-ready infrastructure designed to support everything from traditional applications to AI model training and edge inferencing.</p> <p>UCS products are designed and configured to work together effectively. The goal of a UCS product line is to simplify the number of devices that need to be connected, configured, cooled and secured, enabling administrators to manage everything through a single graphical interface.</p> <p>The term <i>unified computing system</i> is often associated with Cisco. Cisco UCS products support traditional and <a href="https://www.techtarget.com/searchitoperations/definition/virtualization">virtualized</a> environments. Cisco UCS Manager is for on-premises deployments, and Cisco Intersight is for cloud-based management across the entire infrastructure lifecycle.</p> <p>Similar offerings to Cisco UCS include Hewlett Packard Enterprise Synergy and Dell VxRail.</p> A unified computing system (UCS) is a converged data center architecture that integrates computing, networking and storage resources to increase efficiency and enable centralized management. https://cdn.ttgtmedia.com/visuals/digdeeper/6.jpg https://www.techtarget.com/searchdatacenter/definition/unified-computing-system-UCS Tue, 14 Oct 2025 16:15:00 GMT unified computing system (UCS) <p>Mobile application development is the set of processes and procedures involved in writing software for small, wireless computing devices, such as smartphones and other hand-held devices.</p> <p>Like web application development, mobile application development has its roots in more traditional software development. One critical difference, however, is that mobile <a href="https://www.techtarget.com/searchmobilecomputing/definition/app">apps</a> are often written specifically to take advantage of the unique features of a particular mobile device. For example, a gaming app might be written to take advantage of the iPhone's accelerometer, or a mobile health app might be written to take advantage of a smartwatch's temperature sensor.</p> <p>Today, the two most prominent <a href="https://www.techtarget.com/searchmobilecomputing/definition/mobile-operating-system">mobile operating systems</a> are iOS from Apple and Android from Google. Phones and tablets from Apple come preloaded with essential applications, including a full web browser and the Apple App Store. Android devices also come preloaded with similar apps, and the user can install more using the Google Play Store.</p> <section class="section main-article-chapter" data-menu-title="Choosing a mobile application platform"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Choosing a mobile application platform</h2> <p>There are several important considerations when <a href="https://www.techtarget.com/searchmobilecomputing/tip/Comparing-mobile-development-in-iOS-vs-Android">choosing between the iOS and Android platforms</a>. Android, for instance, has more global market share and is strong in Asia, Africa and South America, while iOS is more prevalent in North America, Europe and Japan. The following are some other considerations:</p> <ul class="default-list"> <li>iOS app development is faster, in general, than Android; the latter runs on more devices and therefore requires more testing.</li> <li>Android design requires more different screen sizes than iOS.</li> <li>Apple's Developer Program fee is $99 per year, while Google Play requires only a one-time $25 fee.</li> <li>Google Play's approval process is faster and easier than Apple's App Store.</li> </ul> <p>What about programming languages? IOS app development is primary done with Apple's Swift, although its legacy language, Objective-C, is still around. Xcode is Apple's integrated development environment (<a href="https://www.techtarget.com/searchsoftwarequality/definition/integrated-development-environment">IDE</a>).</p> <p>On the Android side, the preferred Google language is Kotlin, although Java is found in many existing apps. The IDE to use is Android Studio.</p> <p>What about cross-platform development? Facebook's React Native using JavaScript can provide both OSes. Google offers Flutter, which uses the Dart programming language, and Microsoft Xamarin uses .NET and C#. All of these allow a single codebase for use on both the iOS and Android platforms, which can save on development costs.</p> </section> <section class="section main-article-chapter" data-menu-title="Types of mobile applications"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Types of mobile applications</h2> <p>In the early years of mobile apps, the only way to ensure an app could perform optimally on any device was to develop it natively. This meant that new code had to be written specifically for each device's processor. Today, most mobile applications developed are device-agnostic.</p> <p>In the past, if an app needed to be cross-platform and run on multiple OSes, there was little, if any, code that could be reused from the initial development project. Essentially, each device required its own mobile app development project with its own code base. Modern cross-platform tools use common languages such as C# and JavaScript to share code across projects; more importantly, they integrate well with application lifecycle management tools, such as Jenkins. This enables developers to use a single codebase for Apple iOS, Google Android and progressive web apps. <a href="https://www.techtarget.com/whatis/definition/progressive-web-app-PWA">PWAs</a> are built to take advantage of native mobile device features, without requiring the end user to visit an app store, make a purchase and download software locally. Instead, a PWA can be located with a search engine query and accessed immediately through a browser, thereby eliminating the need for e-commerce merchants to develop native apps for multiple mobile OSes.</p> <p>Just like YouTube videos, PWA content is downloaded progressively, which provides the end user with a better user experience than a traditional website that uses responsive design. PWAs are also be referred to as <i>instant mobile apps</i>.</p> <p>Before developing an app, determine which type of app to create. The following highlights several types of mobile app development technologies with information about each:</p> <ul class="default-list"> <li><b>Native applications.</b> These applications are built using IDEs and languages for mobile OSes such as Apple iOS or Google Android. Native apps enable the user to customize necessary features, but they can be more costly than other technologies.</li> <li><b>Hybrid apps.</b> These are web apps that act like native apps. They are developed using technologies such as HTML, JavaScript and <a href="https://www.theserverside.com/definition/cascading-style-sheet-CSS">cascading style sheets</a>. Hybrid apps are more cost-effective to develop than native apps and can be created faster, but they aren't as feature-rich as native applications.</li> <li><b>PWAs. </b>A progressive web app is a website that looks and behaves like a mobile app. These applications are developed using web technologies such as Meta's React.</li> <li><b>Encapsulated apps.</b> An encapsulated app runs within a container app. Products such as the Microsoft Power App drag-and-drop app creation tool enable less experienced developers to build a mobile application rapidly. However, the lack of isolation from the core OS, OS lock-in and relative newness could pose problems.</li> <li><b>Frameworks and libraries.</b> These accelerate the development of mobile apps by using reusable code written by someone else.</li> <li><b>Cross-platform apps.</b> These are like hybrid apps but use frameworks that compile more closely to native code. This enables a single codebase but might limit the use of native features.</li> <li><b>Gaming apps.</b> These can be native, hybrid or cross-platform. Unity and Unreal Engine are popular game engines. Although they are high performance, they can be costly to develop.</li> </ul> </section> <section class="section main-article-chapter" data-menu-title="Costs of developing a mobile app"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Costs of developing a mobile app</h2> <p>The cost of developing an app can range from almost nothing to millions of dollars -- it all depends on the type of app and its intended use. The following is a breakdown of the ranges an organization can expect to pay for building a mobile app:</p> <ul class="default-list"> <li><b>No-code app builders.</b> If the app has basic feature requirements, a developer doesn't need to know how to code. Free tools such as Glide, Softr and Thunkable offer developers the freedom to build apps without learning Swift or other programming languages. Tools such as Adalo and Bubble have pricing plans but offer a free option. Although these tools are limited in their functionality and can't be used to create a game with no-code apps, the no-code approach will meet most organizations' needs.</li> <li><b>Enterprise apps.</b> The concept of <i>citizen developer</i>, where anyone can build a mobile app, is exploding with tools such as Amazon Honeycode, Microsoft Power Platform, OutSystems and SAP Build Apps. These devices offer drag-and-drop interfaces that can connect to data sources and manage content flow. The price is typically tied to a monthly subscription of less than $50.</li> <li><b>Mobile-optimized website. </b>Although it's most practical to build websites for both desktop and mobile devices, the website content management tool an organization uses will likely have plugins they can buy for less than $100 to optimize their website for mobile devices.</li> <li><b>Complex apps.</b> An app that requires features such as three-dimensional graphics, gaming or sophisticated AI will likely need to be developed as a native app. The cost for a complex app can typically be $250,000 or more, and it is directly related to the scarcity of mobile developers.</li> </ul> <figure class="main-article-image full-col" data-img-fullsize="https://www.techtarget.com/rms/onlineimages/app_arch-mobile_app_dev_process-f.png"> <img data-src="https://www.techtarget.com/rms/onlineimages/app_arch-mobile_app_dev_process-f_mobile.png" class="lazy" data-srcset="https://www.techtarget.com/rms/onlineimages/app_arch-mobile_app_dev_process-f_mobile.png 960w,https://www.techtarget.com/rms/onlineimages/app_arch-mobile_app_dev_process-f.png 1280w" alt="An image showing the various steps in the mobile application development process." height="560" width="560"> <figcaption> <i class="icon pictures" data-icon="z"></i>The steps in the mobile app development process involve several key phases. </figcaption> <div class="main-article-image-enlarge"> <i class="icon" data-icon="w"></i> </div> </figure> </section> <section class="section main-article-chapter" data-menu-title="The mobile app development process, step by step"> <h2 class="section-title"><i class="icon" data-icon="1"></i>The mobile app development process, step by step</h2> <p>The following steps should help develop the framework for building an app.</p> <p><b>1.</b> <b>Define a strategy based on the answers to these questions</b>:</p> <ul class="default-list"> <li>What is the objective of the app? What problems will it solve?</li> <li>Are there existing apps that perform this function? If so, what do they do well? What are they lacking?</li> <li>Who is the target audience?</li> <li>Will the organization be hiring developers or using an internal team?</li> <li>What is the business model?</li> <li>How much is the organization willing to invest in developing this app? Will there be investors?</li> <li>How long will it take to build this application?</li> <li>What is the organization's marketing strategy?</li> <li>Is the app being designed for one of the app stores? If so, does the team have the necessary licensing agreements and design and testing criteria?</li> </ul> <p><b>2. Select the development team.</b> Does the organization need to hire a developer, or will the app be designed in-house? What about a marketing person? If this app is being created for the organization, will stakeholders from several departments be participating in the process -- i.e., C-level, marketing, sales or IT?</p> <p><b>3. Brainstorm and sketch.</b> Outline how the mobile app will solve the problems identified and what features and functions to include. Prototyping can be as simple as using a whiteboard or paper to sketch ideas or tools such as Adobe Experience Design, Balsamiq or Invision. When developing the app, keep user experience in mind. This includes design, usability, security and performance.</p> <p><b>4. Develop a product roadmap.</b> Using findings from the previous step, create a step-by-step process for assessing priorities and deliverables.</p> <p><b>5. Select app development tools based on the organization's requirements.</b></p> <p><b>6. Begin app development.</b> An <a href="https://www.techtarget.com/searchsoftwarequality/definition/agile-software-development">Agile process</a> is best for building apps. Adopt a DevOps mindset when building the app. DevOps is a modern delivery methodology that uses key functions, such as the following:</p> <ul class="default-list"> <li>Defining the front-end or client-side. This includes the user interface and navigation.</li> <li>Defining the back-end or server-side. This requires application programming interfaces, authentication and data storage.</li> <li>Applying automation where possible.</li> <li>Using cloud services.</li> <li>Working with open source tools.</li> <li>Frequently communicating with the team.</li> <li>Continuously testing the code.</li> </ul> <p><b>7. Create a prototype that can be shared with investors or other stakeholders.</b> Use their feedback to refine app development and further testing. This includes testing for functionality, performance and ease of navigation.</p> <p><b>8. Roll out the app to users.</b> Once the app passes these tests, it's time to roll it out to users for official <a href="https://www.techtarget.com/whatis/definition/beta-test">beta testing</a>. This process includes multiple rounds of review and incorporating user fixes prior to creating a deployable version of the app.</p> <p>Once the app has undergone the requisite testing and review, it's ready to deploy. At this point, create a channel for user feedback and provide continuous support.</p> <p>Following beta testing, the app must be submitted to the Apple App Store or Google Play Store for review and approval.</p> <p><i>Learn</i><i> </i><a href="https://www.techtarget.com/whatis/feature/How-to-successfully-build-an-app-without-code"><i>what a no-code platform is and how it can be used</i></a><i> to save businesses time and money while being able to deploy more apps at a faster rate.</i></p> </section> Mobile application development is the set of processes and procedures involved in writing software for small, wireless computing devices, such as smartphones and other hand-held devices. https://cdn.ttgtmedia.com/visuals/digdeeper/4.jpg https://www.techtarget.com/searchapparchitecture/definition/mobile-application-development Fri, 10 Oct 2025 00:00:00 GMT What is mobile application development? <p>A REST <a href="https://www.techtarget.com/searchapparchitecture/definition/application-program-interface-API">API</a> is an architectural style for an application programming interface that uses Hypertext Transfer Protocol (<a href="https://www.theserverside.com/blog/Coffee-Talk-Java-News-Stories-and-Opinions/HTTP-methods">HTTP) requests</a> to access and use data. That data can be used to GET, PUT, POST and DELETE data types, which refers to reading, updating, creating and deleting operations related to resources.</p> <p>An API is code that enables two software programs to communicate with one another. The API's design spells out the proper way for a developer to write a program, or client, that uses the API to request services from another application, or the server. APIs are a <a href="https://www.techtarget.com/searchhealthit/feature/Six-Interoperability-Use-Cases-for-APIs-in-Health-Data-Exchange">vital mechanism for software interoperability</a>.</p> <p>REST APIs are also referred to as <a href="https://www.theserverside.com/video/REST-vs-RESTful-API-Whats-the-difference">RESTful web services and RESTful APIs</a>. They're based on <a href="https://www.techtarget.com/searchapparchitecture/definition/REST-REpresentational-State-Transfer">REpresentational State Transfer</a>, an architectural style and approach to communications often used in <a href="https://www.techtarget.com/searchapparchitecture/definition/Web-services">web services</a> development. This approach can also facilitate communication between other application types.</p> <p>REST technology is generally preferred over similar technologies because it uses less bandwidth, making it more efficient for internet use. REST APIs can also be built with common programming languages such as <a href="https://www.techtarget.com/whatis/definition/PHP-Hypertext-Preprocessor">PHP</a>, JavaScript and Python.</p> <p>REST browsers are considered the language of the internet. Cloud consumers use APIs to expose and organize access to web services. REST is a logical choice for building APIs to provide users with ways to flexibly connect to, manage and interact with cloud services in distributed environments. Sites such as Amazon, Google, LinkedIn and Twitter use REST APIs.</p> <div class="youtube-iframe-container"> <iframe id="ytplayer-0" src="https://www.youtube.com/embed/y0U-ZxgLu98?autoplay=0&modestbranding=1&rel=0&widget_referrer=null&enablejsapi=1&origin=https://www.techtarget.com" type="text/html" height="360" width="640" frameborder="0" loading="lazy"></iframe> </div> <section class="section main-article-chapter" data-menu-title="What are the main elements of a REST API, and how does it work?"> <h2 class="section-title"><i class="icon" data-icon="1"></i>What are the main elements of a REST API, and how does it work?</h2> <p>A REST API fundamentally relies on the following three major elements:</p> <ul class="default-list"> <li><b>Client.</b> The client is the software code or application that requests a resource from a server.</li> <li><b>Server.</b> The server is the software code or application that controls the resource and responds to client requests for the resource.</li> <li><b>Resource.</b> The resource is any data or content -- such as text, video and images -- that the server controls and makes available in response to client requests.</li> </ul> <p>To access a resource, the client sends an HTTP request to the server. Client requests include the following four principal parts:</p> <ul class="default-list"> <li><b>HTTP method. </b>This shows what should happen to the specified resource. The four fundamental HTTP methods are known as verbs. POST creates a new resource, GET retrieves an existing resource, PUT updates or changes an existing resource, and DELETE deletes a resource. As the table below shows, these HTTP verbs correspond to the Create, Retrieve, Update and Delete methods or actions, which are referred to as CRUD.</li> <li><b>Endpoint.</b> The endpoint shows where the resource is located and typically includes a Uniform Resource Identifier (<a href="https://www.techtarget.com/whatis/definition/URI-Uniform-Resource-Identifier">URI</a>). If the resource is accessed through the internet, the URI can be a <a href="https://www.techtarget.com/searchnetworking/definition/URL">URL</a> that provides a web address for the resource.</li> <li><b>Header.</b> A header includes the details needed to execute the call and handle the response. A request header might include authentication data, an encryption key, more details about the server location or access information and details about the desired data format needed for the response.</li> <li><b>Body.</b> The body contains relevant information to or from the server. For example, a body might contain the new data to be added to the server through a POST or PUT method.</li> </ul> <table class="main-article-table"> <thead> <tr> <td valign="top" style="width: 121.3pt;"> <p><span style="color: #ecf0f1;">HTTP verb</span></p> </td> <td valign="top" style="width: 121.3pt;"> <p><span style="color: #ecf0f1;">CRUD action</span></p> </td> </tr> </thead> <tbody> <tr> <td valign="top"> <p>POST</p> </td> <td valign="top"> <p>Create</p> </td> </tr> <tr> <td valign="top"> <p>GET</p> </td> <td valign="top"> <p>Read</p> </td> </tr> <tr> <td valign="top"> <p>PUT</p> </td> <td valign="top"> <p>Update</p> </td> </tr> <tr> <td valign="top"> <p>PATCH</p> </td> <td valign="top"> <p>Update</p> </td> </tr> <tr> <td valign="top"> <p>DELETE</p> </td> <td valign="top"> <p>Delete</p> </td> </tr> </tbody> </table> <p>The server-side hosting the API processes the call and forms a response. When data is requested, the server sends a machine-readable representation of the requested data that the client then processes. Usually, response details include any information needed to interpret the response, such as whether the data is in Extensible Markup Language (<a href="https://www.techtarget.com/whatis/definition/XML-Extensible-Markup-Language">XML</a>), JavaScript Object Notation (<a href="https://www.theserverside.com/definition/JSON-Javascript-Object-Notation">JSON</a>) or plain text format. The server provides additional data, such as error codes and time stamps, or other instructions for the client.</p> <p>In short, calls and responses are self-descriptive. This means they will include information on how to process and interpret them.</p> <p>A REST API breaks down a <a href="https://www.techtarget.com/searchcio/definition/transaction">transaction</a> to create a series of small modules. Each module addresses an underlying part of the transaction. This modularity gives developers flexibility, but it can be challenging to <a href="https://www.techtarget.com/searchapparchitecture/tip/16-REST-API-design-best-practices-and-guidelines">design a REST API</a> from scratch. Several organizations and initiatives provide models for developers to use, including Amazon Simple Storage Service, the Storage Networking Industry Association's Cloud Data Management Interface and the OpenStack Foundation's OpenStack Swift.</p> <p>A REST API uses commands to obtain resources. The state of a resource at any given timestamp is called a resource representation. A <a href="https://www.theserverside.com/tip/Idempotent-HTTP-methods-and-REST">REST API uses existing HTTP methodologies</a> that the RFC 2616 protocol defined, such as GET, PUT, POST and DELETE.</p> <p>With REST, networked components are a resource to which the user requests access. This is like a <a href="https://www.techtarget.com/searchsoftwarequality/definition/black-box">black box</a> with unclear implementation details. All calls are <a href="https://www.techtarget.com/whatis/definition/stateless-app">stateless</a>; the REST service can't retain anything between executions.</p> <p>The REST API supports data formats such as application/json, application/xml, application/x-web+xml, application/x-www-form-urlencoded and multipart/form-data.</p> </section> <section class="section main-article-chapter" data-menu-title="What are some examples of REST APIs?"> <h2 class="section-title"><i class="icon" data-icon="1"></i>What are some examples of REST APIs?</h2> <p>Because the calls are stateless, REST is useful in cloud applications. Stateless components can be freely redeployed, resent or retried if something fails, and they provide significant scalability to accommodate workload changes.</p> <p>This approach works because any request can be directed to any instance of a component. Nothing in the next transaction must be remembered, making using REST APIs preferable for web applications.</p> <p>The RESTful model is helpful in cloud services because binding to a service through an API is a matter of controlling how the URL is decoded. Cloud computing and <a href="https://www.techtarget.com/searchapparchitecture/definition/microservices">microservices</a> are almost certain to make RESTful API design the rule in the future.</p> <p>REST APIs are frequently used in mobile and web-based applications to access and change data on remote systems across the internet. There are countless examples of use cases, but the following are some of the most popular:</p> <ul class="default-list"> <li><b>Mobility.</b> Mobile apps such as Lyft and Uber use REST APIs to access maps and schedule rides.</li> <li><b>Google Maps and other geolocation apps.</b> REST APIs retrieve map data to provide locations, distances and directions.</li> <li><b>Weather.</b> REST APIs are commonly used in weather apps, providing current weather conditions, forecasts and historical data.</li> <li><b>Banking and e-commerce.</b> These apps use REST APIs to access account data and support transactions.</li> <li><b>Streaming services.</b> Spotify, Netflix and other streaming services use REST APIs to access media from remote servers.</li> <li><b>Social media.</b> Services such as X and Facebook use REST APIs to make and manage posts as well as to integrate with other applications.</li> </ul> </section> <section class="section main-article-chapter" data-menu-title="Principles of the REST API architectural style: What makes a service RESTful?"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Principles of the REST API architectural style: What makes a service RESTful?</h2> <p>For a service to be considered a true RESTful web API, it must be designed and implemented according to the following client-server architecture principles:</p> <ul class="default-list"> <li><b>The interface must be uniform.</b> This is the most important. All REST APIs must be consistent, providing resource identification in their URIs. They must use standard HTTP methods -- the CRUD operations (GET/POST/PUT, PATCH/DELETE) -- and represent resources in multiple formats, such as XML and JSON.</li> <li><b>Client-server separation.</b> The front end of communication -- the client -- and the back end -- the server -- must be independent of one another; the server must provide the resources, while the client hosts the UI.</li> <li><b>Multiple layers.</b> Though not required, the architecture allows for multiple layers, including proxies, load balancers and authentication; the client doesn't care if it's actually communicating with the web server.</li> <li><b>It must be stateless. </b>Each API call is independent, meaning the server does not track the client's state between requests.</li> <li><b>Caching.</b> Responses use HTTP headers to determine whether they are cacheable; this reduces latency and improves performance.</li> <li><b>Code return.</b> Though not required, the architecture enables the server to return executable code to the client, such as JavaScript, if it is useful.</li> </ul> </section> <section class="section main-article-chapter" data-menu-title="What are the benefits of REST APIs?"> <h2 class="section-title"><i class="icon" data-icon="1"></i>What are the benefits of REST APIs?</h2> <p>REST APIs have gained enormous popularity due to the numerous benefits they provide developers and organizations, including the following:</p> <ul class="default-list"> <li><b>Simplicity.</b> REST APIs use common HTTP methods, including GET, PUT, POST and DELETE requests, making them easy to design, implement and use.</li> <li><b>Independence.</b> Developers enjoy platform independence because they can use almost any programming language to create REST APIs. They work with various client devices, such as traditional web browsers, mobile devices and internet of things devices.</li> <li><b>Flexible.</b> REST APIs support many different data formats, including JSON, XML and plain text. Developers can choose the data format that best suits their client's needs and available server-side data.</li> <li><b>Scalable.</b> The stateless nature of REST APIs supports horizontal scaling, where many API calls run in parallel to handle significant API call loads.</li> <li><b>Cacheable.</b> REST APIs support caching, allowing data to be stored in local memory. This approach can speed server-side response time, potentially improving API performance. It might even eliminate the need for an API call if required data is already on the client from a prior call.</li> <li><b>Secure.</b> REST APIs can secure calls and data exchanges with Open Authorization (<a href="https://www.techtarget.com/searchapparchitecture/definition/OAuth">OAuth</a>) authentication and Secure Sockets Layer/Transport Layer Security encryption.</li> <li><b>Compatible.</b> Proper use of <a href="https://www.techtarget.com/searchsoftwarequality/definition/versioning">versioning</a> lets developers treat APIs like any other evolving software, adding new features over time with backward compatibility and supporting legacy features for existing clients.</li> </ul> </section> <section class="section main-article-chapter" data-menu-title="RESTful API design and architecture constraints and challenges"> <h2 class="section-title"><i class="icon" data-icon="1"></i>RESTful API design and architecture constraints and challenges</h2> <p>Dr. Roy T. Fielding, senior principal scientist at Adobe, defined RESTful API design in his 2000 doctoral dissertation as a web service that adheres to the following six REST architectural constraints:</p> <ul class="default-list"> <li><b>A uniform interface.</b> Resources should be uniquely identifiable through a single URL. Manipulating a resource should occur only using the network protocol methods DELETE, PUT and GET with HTTP.</li> <li><b>Client-server based.</b> The delineation between the client and server should be clear. The client's domain is the UI and request-gathering concerns, while the server's domain is data access, workload management and security. This loose coupling of the client and server enables each to be developed and enhanced independently of the other.</li> <li><b>Stateless operations</b>. All client-server operations must be stateless. Any state management required should occur on the client, not the server.</li> <li><b>RESTful resource caching.</b> All resources should allow <a href="https://www.techtarget.com/whatis/definition/caching">caching</a> unless that isn't possible.</li> <li><b>Layered system.</b> REST enables an architecture composed of multiple layers of servers.</li> <li><b>Code on demand</b>. Usually, a server will send back static representations of resources in the form of XML or JSON. However, when necessary, servers can send executable code to the client.</li> </ul> <p>REST APIs aren't a panacea. Some concepts that might be challenging include the following:</p> <ul class="default-list"> <li><b>Endpoint consistency.</b> To be consistent, endpoint paths should follow common web standards, which might be difficult to manage.</li> <li><b>API versioning.</b> Endpoint URLs shouldn't be invalidated when used internally or with other applications.</li> <li><b>Long response times and too much data.</b> The amount of returned resources can grow over time, increasing load and response times.</li> <li><b>Navigation paths and user input locations.</b> Because REST uses URL paths for input parameters, determining URL spaces can be challenging.</li> <li><b>Security.</b> There are many security issues to manage, such as the use of HTTPS, blocking access from unknown IP addresses and domains, validating URLs, blocking unexpectedly large payloads, monitoring and logging requests, and investigating failures.</li> <li><b>Authentication.</b> This requires awareness and use of <a href="https://www.techtarget.com/searchapparchitecture/tip/5-fundamental-strategies-for-REST-API-authentication">common authentication methods</a> such as HTTP basic authentication, which allows for a base64-encoded username and password string; API keys; JSON Web Tokens; and other access tokens, such as OAuth 2.0, which is good for <a href="https://www.techtarget.com/searchsecurity/definition/access-control">access control</a>.</li> <li><b>Requests and data.</b> Some requests might contain more data and metadata than needed, or more requests might be needed to obtain all the data. APIs can be adjusted for this.</li> <li><b>Error codes and messages. </b>A common practice is to use standard HTTP error codes. Error handling might not be able to distinguish whether a response is successful, besides parsing the body or checking for an error.</li> <li><b>API testing.</b> This might be a long process to set up and run, and each part can be challenging. Testing can also occur on the command line with the client URL, or cURL, utility. Testing-related challenges include the initial setup, <a href="https://www.techtarget.com/searchdatamanagement/definition/schema">schema</a> updates, test parameter combinations, sequencing of API calls, validation of test parameters and system integration.</li> </ul> </section> <section class="section main-article-chapter" data-menu-title="REST API best practices"> <h2 class="section-title"><i class="icon" data-icon="1"></i>REST API best practices</h2> <p>REST APIs are dedicated software applications designed to support network communication and execution of specific tasks. API development and management are often approached using the same principles and guidelines applied to any other software project. However, the following common REST API best practices can improve API designs and implementations:</p> <ul class="default-list"> <li><b>Use nouns in endpoint paths.</b> Where a REST API already employs a verb, such as GET or PUT, in the formation of a request, the resource being accessed should use a noun designation, like GET/datasource or POST/articles. This makes request formation more intuitive for designers.</li> <li><b>Use a well-established data format.</b> JSON is the most common and popular data format for REST API payloads and the default format for popular programming languages such as JavaScript.</li> <li><b>Employ graceful error handling.</b> Be sure to include complete error handling in REST API responses and use standard HTTP response codes to indicate error type. This helps ensure that errors don't crash the client app or server, and they can be understood and corrected quickly.</li> <li><b>Restrict data sets.</b> Use filtering, sorting and other data access techniques to restrict or reduce the volume of data that can be returned to a client. Trying to transfer huge data sets can impair or crash the API. Design the API to request and send only the minimum data requested.</li> <li><b>Maintain security.</b> Design the REST API to use both authentication and encryption as standard practices. Comprehensive security should be applied even to public APIs using freely available data.</li> <li><b>Use caching wherever possible.</b> REST API supports caching on the server and client sides. Using cache on the server side speeds up the server's response time when a frequent request arrives. Using cache on the client side means the data is already on the client and does not need to make the API call. In both cases, API performance improves.</li> </ul> </section> <section class="section main-article-chapter" data-menu-title="REST vs. SOAP"> <h2 class="section-title"><i class="icon" data-icon="1"></i>REST vs. SOAP</h2> <p>REST and <a href="https://www.techtarget.com/searchapparchitecture/definition/SOAP-Simple-Object-Access-Protocol">Simple Object Access Protocol</a> offer different methods to invoke a web service. REST is an architectural style, while SOAP defines a standard communication protocol specification for XML-based message exchange. REST applications can use SOAP.</p> <p>RESTful web services are stateless. A REST-based implementation is simple compared to SOAP. However, users must understand the context and content being passed along. There's no standard set of rules to describe the REST web services interface. REST services are useful for restricted profile devices, such as mobile devices, and are easy to integrate with existing websites.</p> <p>SOAP requires less plumbing code -- the low-level, infrastructural code that connects main code modules together -- than REST services design. The Web Services Description Language describes a common <a target="_blank" href="https://www.w3.org/TR/wsdl20/" rel="noopener">set of rules</a> to define the messages, bindings, operations and locations of the service. SOAP web services are useful for asynchronous processing and invocation. The structured formality found in SOAP is often better-suited to complex enterprise-level software integrations and workflows that might overwhelm the design of a similar REST API.</p> <p>REST and SOAP are both useful and effective methods for building APIs. Choosing between them depends on the API's intended purpose and characteristics.</p> </section> <section class="section main-article-chapter" data-menu-title="History of RESTful APIs"> <h2 class="section-title"><i class="icon" data-icon="1"></i>History of RESTful APIs</h2> <p>Prior to REST, developers used SOAP to integrate APIs. To make a call, developers handwrote an XML document with a <a href="https://www.techtarget.com/searchapparchitecture/definition/Remote-Procedure-Call-RPC">Remote Procedure Call</a> in the body. They then specified the endpoint and would POST their SOAP envelope to the endpoint.</p> <p>In 2000, Dr. Fielding and a group of developers decided to create a standard so that any server could talk to any other server. He defined REST, which has universal rules that make it easier for developers to integrate software.</p> <p><a href="https://www.techtarget.com/searchcustomerexperience/definition/Salesforcecom">Salesforce</a> was the first company to sell a RESTful API as part of its internet-as-a-service package in 2000. However, few developers were able to use the complicated XML API. Then eBay built a REST API, which expanded its market to any site that could access its API. This caught the attention of another e-commerce giant, and Amazon announced its API in 2002.</p> <p>Flickr launched its RESTful API in August 2004, letting bloggers easily embed images on their sites and social media feeds. Facebook and Twitter both released their APIs in 2006, buckling under the pressure of developers who scraped the sites and created <i>Frankenstein APIs</i>. When AWS helped launch the cloud in 2006, developers could access data space in minutes using its REST API. The request for public APIs quickly escalated.</p> <p>Since then, developers have embraced REST APIs, using them to add functionality to their websites and applications. Today, they are considered the backbone of the internet.</p> <p><i>Bad actors can target REST applications. Learn how to <a href="https://www.techtarget.com/searchsecurity/tip/8-best-practices-for-securing-RESTful-APIs">protect RESTful APIs from attackers</a>. </i></p> </section> A REST API is an architectural style for an application programming interface that uses Hypertext Transfer Protocol (HTTP) requests to access and use data. https://cdn.ttgtmedia.com/visuals/digdeeper/4.jpg https://www.techtarget.com/searchapparchitecture/definition/RESTful-API Tue, 30 Sep 2025 11:15:00 GMT What is a REST API? Benefits, Uses, Examples <p>Data stewardship is the management and oversight of an organization's data assets, which helps provide business users with high-quality, easily accessible and consistent data. While <a href="https://www.techtarget.com/searchdatamanagement/definition/data-governance">data governance</a> focuses on high-level policies and procedures, data stewardship focuses on tactical coordination and implementation.</p> <p>Data stewards are responsible for data use and security policies determined by enterprise data governance initiatives. They typically are the liaison between the IT department and the business side of an organization.</p> <p>The role requires various technical and business skills, including programming and data modeling. Data stewards are also versed in areas such as data warehousing, storage and enterprise strategy. Strong communication and collaboration skills are required for the role.</p> <p>Some organizations have created formal data steward positions, often filling them with people drawn from various business units. Others assign stewardship responsibilities to employees who also have other duties.</p> <p>A data steward might function as a data coordinator, who tracks data movement inside an organization, and a data corrector, who understands and enforces internal rules on how data can be used. Regardless of how the position is structured, an effective data steward maintains agreed-upon data definitions and formats, identifies <a href="https://www.techtarget.com/searchdatamanagement/definition/data-quality">data quality</a> issues and ensures that business users adhere to specified data standards.</p> <p>An organization might have a data stewardship program as part of its overall <a href="https://www.techtarget.com/searchstorage/definition/data-life-cycle-management">data lifecycle management</a> effort or to help with data quality improvement projects. A data steward often collaborates with data architects; business intelligence developers; <a href="https://www.techtarget.com/searchdatamanagement/definition/Extract-Load-Transform-ELT">extract, transform and load</a> designers; business data owners; and others to uphold data consistency and quality metrics. Data quality tools and data profiling software are key technology components of many data stewardship programs.</p> <figure class="main-article-image full-col" data-img-fullsize="https://www.techtarget.com/rms/onlineImages/data_management-who_data_governance-f.png"> <img data-src="https://www.techtarget.com/rms/onlineImages/data_management-who_data_governance-f_mobile.png" class="lazy" data-srcset="https://www.techtarget.com/rms/onlineImages/data_management-who_data_governance-f_mobile.png 960w,https://www.techtarget.com/rms/onlineImages/data_management-who_data_governance-f.png 1280w" alt="Illustrated chart with descriptions of data governance team roles and responsibilities." height="358" width="559"> <figcaption> <i class="icon pictures" data-icon="z"></i>Data stewards are part of the data governance team, which also includes data quality analysts and chief data officers. </figcaption> <div class="main-article-image-enlarge"> <i class="icon" data-icon="w"></i> </div> </figure> <section class="section main-article-chapter" data-menu-title="Why is data stewardship important?"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Why is data stewardship important?</h2> <p>The data steward position -- and, in fact, information governance overall -- emerged as a critical role in the second decade of the 21st century. At that time, data and the information it yields started becoming more valuable. Organizations increasingly rely on data and the insights gleaned from it to make strategic decisions, drive tactical activities and support <a href="https://www.techtarget.com/searchcio/definition/digital-transformation">digital transformation</a> efforts.</p> <p>Data must be accurate, current and accessible to executives, managers and line workers when and where they need it. This enables them to make data-driven decisions. Accurate and accessible data also drives technology initiatives, such as machine learning and artificial intelligence (<a href="https://www.techtarget.com/searchenterpriseai/definition/AI-Artificial-Intelligence">AI</a>) programs that depend on data to work.</p> </section> <section class="section main-article-chapter" data-menu-title="Roles and responsibilities of a data steward"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Roles and responsibilities of a data steward</h2> <p>Data steward responsibilities include inventorying corporate data, determining how to access it and identifying where it's needed. They typically are tasked with ensuring its accuracy and availability. However, data steward responsibilities can also include helping to identify and articulate ways to use company data to create competitive advantages in the market.</p> <p>The roles and responsibilities of a data steward vary based on the maturity of the data program within an organization. For data stewards whose positions are new to an organization and where data governance is in its early stages, their duties might be tasks aimed at consolidating data from multiple databases and platforms. They might also be charged with establishing processes to manage data best.</p> <p>Data stewards at companies with more mature data programs, where that foundational work has been done, are typically focused on higher-value tasks. These can include ensuring the quality of the data, managing <a href="https://www.techtarget.com/searchdatamanagement/definition/compliance">compliance</a> with data standards and policies as established by the governance program, and advocating for data use cases within the business.</p> <p>In general, data stewards' duties include the following:</p> <ul class="default-list"> <li>Managing data from a variety of sources.</li> <li>Guaranteeing the quality of the data the organization collects, stores and uses.</li> <li>Documenting and enforcing rules around data collection, storage and use.</li> <li>Executing the policies and standards in the organization's data governance program.</li> <li>Ensuring access to the right data by the right users at the right time based on whether information is private, corporate or sensitive.</li> <li>Helping to create and implement processes and procedures for data collection, storage, use and security.</li> <li>Identifying ways to use data to drive enterprise objectives.</li> </ul> <p>Data stewards are accountable for managing all data collected and used by the enterprise and ensuring that the data-related rules established by the data governance program are followed.</p> <div class="youtube-iframe-container"> <iframe id="ytplayer-0" src="https://www.youtube.com/embed/BqdPuwvwPk4?autoplay=0&modestbranding=1&rel=0&widget_referrer=null&enablejsapi=1&origin=https://www.techtarget.com" type="text/html" height="360" width="640" frameborder="0" loading="lazy"></iframe> </div> </section> <section class="section main-article-chapter" data-menu-title="What are the benefits of data stewardship?"> <h2 class="section-title"><i class="icon" data-icon="1"></i>What are the benefits of data stewardship?</h2> <p>Data stewardship programs help organizations in several ways. The following are some of the <a href="https://www.techtarget.com/searchdatamanagement/tip/5-benefits-of-building-a-strong-data-governance-strategy">benefits of a data stewardship</a> program:</p> <ul class="default-list"> <li>Improved data quality.</li> <li>Better data documentation.</li> <li>Clear, concise data policies and processes.</li> <li>Efficient and effective analytics programs.</li> <li>Frequent use of data to make decisions.</li> <li>Improved compliance with data-related regulations.</li> <li>Fewer errors in processes and decisions driven by data.</li> <li>Reduced risks around data-related security and privacy requirements.</li> </ul> </section> <section class="section main-article-chapter" data-menu-title="Challenges of data stewardship"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Challenges of data stewardship</h2> <p>Data stewardship involves several challenges, including the following:</p> <ul class="default-list"> <li><b>Privacy and confidentiality.</b> Data stewards must protect sensitive customer data, such as personal details, in a data domain regulated by protections such as the European Union's <a href="https://www.techtarget.com/whatis/definition/General-Data-Protection-Regulation-GDPR">General Data Protection Regulation</a>.</li> <li><b>Inconsistent data quality.</b> Variations in data quality across systems or departments can degrade data integrity, making it difficult for stewards to standardize and maintain reliable data governance.</li> <li><b>Resource limitations.</b> Stewardship requires organizational investment in time, tools and skilled staff. If the proper investments aren't made, data custodians might be unable to manage large, complex data domains.</li> <li><b>Resistance to change.</b> Employees or teams might resist adopting new processes and tools outlined in the framework, slowing efforts to implement best practices.</li> <li><b>Compliance issues.</b> Data stewards must adapt quickly to constantly shifting legal and industry standards to avoid costly governance gaps. The cost of a data breach in 2024 was $4.88 million, <a target="_blank" href="https://www.ibm.com/think/insights/cost-of-a-data-breach-2024-financial-industry" rel="noopener">according to IBM</a>.</li> </ul> </section> <section class="section main-article-chapter" data-menu-title="Uses of a data stewardship program"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Uses of a data stewardship program</h2> <p>An organization might have a single data steward or multiple professionals in this role. How it does this depends on its size, the criticality of its data needs, the maturity of its data program, its industry and its business objectives. Organizations with multiple data stewards might assign them to business units or certain data types.</p> <p>Uses of a data stewardship program include oversight and management of the following:</p> <ul class="default-list"> <li>Enterprise data efforts and operations, including data lifecycle management, which establishes and enforces how long data is retained.</li> <li>Data quality programs, including establishing and using quality metrics and quality detection and correction procedures.</li> <li><a href="https://www.techtarget.com/searchcio/definition/data-privacy-information-privacy">Data privacy</a>, security and risk management according to standards set in conjunction with the data governance program, the security team, the legal department and the risk function, including the implementation and monitoring of controls.</li> <li>Enterprise policies and procedures for accessing data to ensure authorized users have access to data at the time and in the format they need it, and in a way that ensures the confidentiality and integrity of the data.</li> </ul> <p>The data stewardship program works in conjunction with the data governance program. Data governance is the group that sets the enterprise's objectives, risk tolerance, security requirements and strategic needs regarding data.</p> <p>Data stewards also work with the organization's data owners, who are typically senior managers and department heads responsible for identifying the data their respective functions need and understanding how their functions will use data to achieve the business's goals. The data can include corporate data and data obtained elsewhere.</p> </section> <section class="section main-article-chapter" data-menu-title="Data steward vs. data analyst vs. data scientist"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Data steward vs. data analyst vs. data scientist</h2> <p>Organizations with data stewards expect them to work closely with the data analysts and <a href="https://www.techtarget.com/searchenterpriseai/definition/data-scientist">data scientists</a> who access and analyze data to understand past trends, identify patterns and predict future outcomes.</p> <p>While all three professionals handle data, data stewards aren't the same as data analysts and data scientists. Data analysts and scientists retrieve and organize data to analyze and manipulate it to gain insights and draw conclusions.</p> <p>They use data to produce reports on an organization's performance and current state, helping business leaders make data-driven decisions.</p> <p>Data analysts and scientists use data to glean insights into future outcomes. They also use data for <a href="https://www.techtarget.com/searchbusinessanalytics/definition/predictive-analytics">predictive analytics</a>, such as determining the most likely outcomes as they change and adjust different variables within the scenario.</p> <p>Organizations must use data to remain competitive. Industries such as banking and retail see data as critical to delivering services and goods. Moreover, some industries see their use of data as central to their existence. Health systems, for instance, increasingly rely on data and analytics to ensure the best patient outcomes. In addition, emerging fields, such as robotics and AI, exist solely because of the data they're built on. These factors make data stewards an essential part of a modern enterprise team.</p> <figure class="main-article-image full-col" data-img-fullsize="https://www.techtarget.com/rms/onlineImages/data_management-need_to_govern_data-f.png"> <img data-src="https://www.techtarget.com/rms/onlineImages/data_management-need_to_govern_data-f_mobile.png" class="lazy" data-srcset="https://www.techtarget.com/rms/onlineImages/data_management-need_to_govern_data-f_mobile.png 960w,https://www.techtarget.com/rms/onlineImages/data_management-need_to_govern_data-f.png 1280w" alt="Bullet list chart of six reasons data governance is important." height="283" width="560"> <figcaption> <i class="icon pictures" data-icon="z"></i>Data governance is a critical aspect of running an organization and can prevent data silos and secure critical data. </figcaption> <div class="main-article-image-enlarge"> <i class="icon" data-icon="w"></i> </div> </figure> </section> <section class="section main-article-chapter" data-menu-title="Data stewardship vs. data governance"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Data stewardship vs. data governance</h2> <p>Data stewardship involves hands-on data management. Successful data stewardship ensures accuracy, accessibility and quality within a specific data domain, such as customer records or financial metrics. It also ensures that data aligns with business needs and remains reliable for decision-making.</p> <p>On the other hand, data governance involves creating the larger <a href="https://www.techtarget.com/searchdatamanagement/tip/5-data-governance-framework-examples">governance framework</a> that data stewards adhere to. This includes defining policies, standards and data governance rules across an organization. Data governance is the overarching system that outlines who owns data, how it's used and what best practices must be enforced. Data stewards put all this into action within specific domains, such as customer insights or operational logs.</p> <p><i>Data stewardship is part of the enterprise's overall data governance framework. Learn about the </i><a href="https://www.techtarget.com/searchdatamanagement/feature/15-top-data-governance-tools-to-know-about"><i>top data governance tools</i></a><i>.</i></p> </section> Data stewardship is the management and oversight of an organization's data assets, which helps provide business users with high-quality, easily accessible and consistent data. https://cdn.ttgtmedia.com/visuals/digdeeper/3.jpg https://www.techtarget.com/searchdatamanagement/definition/data-stewardship Tue, 16 Sep 2025 00:00:00 GMT What is data stewardship? <p>Clinical trials, also known as clinical research studies, are carefully designed investigations involving volunteer human participants to evaluate the safety, efficacy and outcomes of medical or surgical interventions. These interventions can include experimental drugs, <a href="https://www.techtarget.com/pharmalifesciences/news/366607906/Women-are-underrepresented-in-medical-device-clinical-trials">devices</a>, therapies, diagnostic tools, vaccines, procedures or lifestyle modifications such as diet or exercise.</p> <p>Clinical trials are a fundamental component of medical research. They are typically <a href="https://www.techtarget.com/pharmalifesciences/feature/Developing-Clinical-Trial-Budgets-Considerations-and-Best-Practices">funded or sponsored</a> by government agencies (e.g., the National Institutes of Health), pharmaceutical companies, biotechnology firms, academic institutions or nonprofit organizations. Their primary goal is to <a href="https://www.techtarget.com/pharmalifesciences/feature/How-AI-is-revolutionizing-clinical-trials-drug-development">generate scientific evidence</a> that informs regulatory decisions, clinical practice and future research.</p> <section class="section main-article-chapter" data-menu-title="Why clinical trials are important"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Why clinical trials are important</h2> <p>Clinical trials are critical for <a href="https://www.techtarget.com/pharmalifesciences/feature/Understanding-the-Value-Complexity-of-Clinical-Trials-in-the-US">advancing medical science and public health</a>. They help determine the following:</p> <ul class="default-list"> <li>Whether a new drug, device or treatment is safe and works as intended.</li> <li>How a treatment compares to standard therapies.</li> <li>What side effects may occur and how to manage them.</li> <li>Proper dosage levels and administration frequency.</li> <li>Drug interactions with food, other medications or health conditions.</li> </ul> <p>By rigorously evaluating new interventions, clinical trials <a href="https://www.techtarget.com/pharmalifesciences/news/366606701/Integrating-Real-World-and-Clinical-Trial-Data-to-Improve-Patient-Outcomes">provide the data needed</a> to balance benefits against risks. This evidence helps regulatory bodies assess new therapies and allows healthcare providers to make informed treatment decisions.</p> <div class="youtube-iframe-container"> <iframe id="ytplayer-0" src="https://www.youtube.com/embed/Zvm3skSY9RA?autoplay=0&modestbranding=1&rel=0&widget_referrer=null&enablejsapi=1&origin=https://www.techtarget.com" type="text/html" height="360" width="640" frameborder="0" loading="lazy"></iframe> </div> </section> <section class="section main-article-chapter" data-menu-title="Regulation of clinical trials"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Regulation of clinical trials</h2> <p>Clinical trials are tightly regulated in the U.S to protect participants and ensure <a href="https://www.techtarget.com/searchdatacenter/definition/integrity">data integrity</a>. In U.S.-based research, regulatory bodies perform different functions:</p> <ul class="default-list"> <li><b>Food and Drug Administration (</b><a href="https://www.techtarget.com/searchhealthit/definition/FDA-US-Food-and-Drug-Administration">FDA</a><b>):</b> The FDA evaluates the safety and effectiveness of drugs, biologics and devices.</li> <li><b>National Institutes of Health (NIH)</b>. The NIH is the world's largest public funder of biomedical research. It also sets guidelines for research conduct, data and safety monitoring, and other practices.</li> <li><b>Institutional Review Boards (IRBs)</b>. Typically based in the host institution conducting the trial, IRBs are administrative bodies that review and approve clinical trial protocols to ensure ethical treatment of participants.</li> </ul> <p>The FDA's Center for Drug Evaluation and Research oversees drug trials and requires all new therapies to undergo clinical testing before market approval. Other countries maintain their own regulatory frameworks, such as the Medicines and Healthcare Products Regulatory Agency in the U.K. or the National Medical Products Administration in China.</p> </section> <section class="section main-article-chapter" data-menu-title="Clinical trial phases"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Clinical trial phases</h2> <p>Clinical trials typically proceed through a <a href="https://www.techtarget.com/pharmalifesciences/news/366607518/Breaking-Down-the-Stages-of-Clinical-Trials-Their-Challenges">series of phases</a> to assess different aspects of a treatment's safety and effectiveness:</p> <h3>Phase 0 (Exploratory or Early Phase I)</h3> <ul class="default-list"> <li>Small group (fewer than 15 participants).</li> <li>Goal: micro-dosing to understand pharmacokinetics and preliminary human response.</li> <li>Not always required, but can streamline <a href="https://www.techtarget.com/pharmalifesciences/news/366606452/Understanding-the-Pharmaceutical-Drug-Development-Life-Cycle">drug development</a>.</li> </ul> <h3>Phase I</h3> <ul class="default-list"> <li>From 15 to 30 participants (healthy volunteers or patients).</li> <li>Goal: Determine safe dosage range and identify side effects.</li> <li>Focus on safety rather than efficacy.</li> </ul> <figure class="main-article-image full-col" data-img-fullsize="https://www.techtarget.com/rms/onlineimages/healthit-clinical-trial.png"> <img data-src="https://www.techtarget.com/rms/onlineimages/healthit-clinical-trial_mobile.png" class="lazy" data-srcset="https://www.techtarget.com/rms/onlineimages/healthit-clinical-trial_mobile.png 960w,https://www.techtarget.com/rms/onlineimages/healthit-clinical-trial.png 1280w" alt="Visual representation of clinical trial phases, detailing Phase 0 through IV, highlighting key objectives and processes." height="254" width="520"> <figcaption> <i class="icon pictures" data-icon="z"></i>Experimental treatments undergo progressively rigorous testing to validate efficacy and safety, paving the way for regulatory approval. </figcaption> <div class="main-article-image-enlarge"> <i class="icon" data-icon="w"></i> </div> </figure> <h3>Phase II</h3> <ul class="default-list"> <li>From 25 to 100 participants.</li> <li>Goal: evaluate treatment efficacy and continue <a href="https://www.techtarget.com/pharmalifesciences/feature/Considerations-in-Pediatric-Clinical-Trials-Ensuring-Patient-Safety">safety monitoring</a>.</li> <li>May include multiple treatment arms and protocols.</li> </ul> <h3>Phase III</h3> <ul class="default-list"> <li>More than 100 participants across multiple sites.</li> <li>Goal: compare new treatment to current standard of care.</li> <li>Can include randomized, double-blind, placebo-controlled study designs.</li> <li>Results form the basis of regulatory approval.</li> </ul> <h3>Phase IV</h3> <ul class="default-list"> <li>Conducted after a treatment is approved and commercially available.</li> <li>Goal: monitor long-term effects and gather additional <a href="https://www.techtarget.com/pharmalifesciences/feature/Revolutionizing-Clinical-Trial-Data-Tracking-Analysis-with-Technology">safety and efficacy data</a> in real-world populations.</li> </ul> <p>On average, the <a href="https://www.techtarget.com/pharmalifesciences/answer/Addressing-Clinical-Trial-Challenges-and-High-Drug-Development-Costs">full clinical trial process</a> can take up to 10 years and cost hundreds of millions or even billions of dollars.</p> </section> <section class="section main-article-chapter" data-menu-title="Clinical trial vs. clinical study"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Clinical trial vs. clinical study</h2> <p>A clinical study is any research involving human participants with the goal of <a href="https://www.techtarget.com/pharmalifesciences/feature/How-Do-Various-Stakeholders-Define-Clinically-Meaningful-Data">gaining medical knowledge</a>. There are two primary types:</p> <ul class="default-list"> <li><b>Interventional studies (clinical trials)</b>. Researchers assign participants to receive specific interventions to measure outcomes.</li> <li><b>Observational studies</b>. Researchers observe health outcomes in participants without assigning specific interventions.</li> </ul> <p>For example, a clinical trial might assign one group to receive a new drug and another to receive a placebo. At the same time, an observational study might follow patients taking various treatments prescribed by their physicians.</p> </section> <section class="section main-article-chapter" data-menu-title="Randomized controlled trials (RCTs)"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Randomized controlled trials (RCTs)</h2> <p>A <a href="https://www.techtarget.com/pharmalifesciences/feature/Understanding-the-importance-of-randomized-clinical-trials">randomized controlled trial</a> is the gold standard for evaluating treatment efficacy. In an RCT, the following conditions must be met:</p> <ul class="default-list"> <li>Participants are randomly assigned to intervention or control groups.</li> <li>Neither the patient nor the clinician (in double-blind studies) knows which group the patient is in.</li> <li>Results are compared to determine the effect of the treatment.</li> </ul> <p>This approach helps eliminate selection bias and increases the reliability of results.</p> </section> <section class="section main-article-chapter" data-menu-title="Eliminating bias in clinical trials"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Eliminating bias in clinical trials</h2> <p>Researchers use several strategies to <a href="https://www.techtarget.com/searchhealthit/news/366578706/How-EHR-Data-Survey-Responses-Can-Mitigate-Clinical-Research-Bias">reduce bias</a> and ensure reliable data:</p> <ul class="default-list"> <li><b>Randomization</b>: Ensures comparable groups.</li> <li><b>Blinding:</b> Keeps participants and/or researchers unaware of group assignments.</li> <li><b>Placebo control</b>: Allows comparison against an inactive treatment.</li> <li><b>Standardized protocols</b>: Ensures consistent treatment across sites.</li> </ul> <p>These methods help protect the integrity of the trial and ensure that findings are based on objective results.</p> </section> <section class="section main-article-chapter" data-menu-title="Who can participate in a clinical trial?"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Who can participate in a clinical trial?</h2> <p>Clinical trials include eligibility criteria that define who can or cannot participate. Criteria may include a range of factors:</p> <ul class="default-list"> <li>Age, sex or specific health conditions</li> <li>Stage of disease</li> <li>Previous treatment history</li> <li>Laboratory test results</li> </ul> <p>Participants must provide <a href="https://www.techtarget.com/searchhealthit/news/366577831/Electronic-Informed-Consenting-Improves-Data-for-Clinical-Research">informed consent</a>, which affirms that they understand the trial's purpose, procedures, potential risks and benefits before enrolling.</p> <p>Participation is voluntary, and subjects may withdraw at any time.</p> </section> <section class="section main-article-chapter" data-menu-title="Where to find clinical trials"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Where to find clinical trials</h2> <p>Individuals interested in joining a clinical trial can search various websites:</p> <ul class="default-list"> <li><b>ClinicalTrials.gov</b>. A database of federally and privately supported clinical trials in the U.S. and globally.</li> <li><b>ResearchMatch.org</b>. An NIH-funded nonprofit that connects volunteers with approved studies.</li> <li><b>Cancer.gov</b>. Contains a searchable database of clinical trials funded by the National Cancer Institute.</li> <li><b>Hospital websites</b>. Many academic and regional medical centers list ongoing trials.</li> </ul> <p>Patients should consult with their healthcare providers to discuss trial participation and suitability.</p> <p><i>Learn about the </i><a href="https://www.techtarget.com/pharmalifesciences/feature/Exploring-5-types-of-clinical-trial-data-sharing-platforms"><i>five main types of clinical trial data-sharing platforms</i></a><i> -- trial registries, results repositories, open data platforms, sponsor-specific and consortium-based platforms.</i></p> </section> Clinical trials, also known as clinical research studies, are carefully designed investigations involving volunteer human participants to evaluate the safety, efficacy and outcomes of medical or surgical interventions. https://cdn.ttgtmedia.com/visuals/digdeeper/6.jpg https://www.techtarget.com/searchhealthit/definition/clinical-trial Fri, 12 Sep 2025 11:30:00 GMT What is a clinical trial? <p>OCR (optical character recognition) is the use of technology to distinguish printed or handwritten text characters inside digital images of physical documents, such as a scanned paper document. The basic process of OCR involves examining the text of a document and translating the characters into <a href="https://www.techtarget.com/whatis/definition/code">code</a> that can be used for <a href="https://www.techtarget.com/searchdatabackup/definition/data-processing">data processing</a>. OCR is sometimes referred to as text recognition.</p> <p>OCR systems consist of a combination of hardware and software that is used to convert physical documents into machine-readable text. Hardware, such as an optical <a href="https://www.techtarget.com/whatis/definition/scanner">scanner</a> or specialized <a href="https://www.techtarget.com/whatis/definition/printed-circuit-board-PCB">circuit board</a>, is used to copy or read text while software typically handles the advanced processing. Software can also take advantage of <a href="https://www.techtarget.com/searchenterpriseai/definition/AI-Artificial-Intelligence">AI</a> to implement more advanced methods of intelligent character recognition (<a href="https://klearstack.com/intelligent-character-recognition-software" target="_blank" rel="noopener">ICR</a>), like identifying languages or styles of handwriting.</p> <p>OCR is most commonly used to convert hard copies of legal or historical documents into <a href="https://www.techtarget.com/whatis/definition/Portable-Document-Format-PDF">PDFs</a>. Once the document is in this <a href="https://www.techtarget.com/whatis/definition/soft-copy">soft copy</a>, users can edit, format and search it as if it were created with a word processor.</p> <section class="section main-article-chapter" data-menu-title="How optical character recognition works"> <h2 class="section-title"><i class="icon" data-icon="1"></i>How optical character recognition works</h2> <p>The first step of OCR is using a scanner to process a document's physical form. Once all pages are copied, OCR software converts the document into a two-color, or black-and-white, version. The scanned-in image or <a href="https://www.techtarget.com/whatis/definition/bit-map">bitmap</a> is analyzed for light and dark areas, where the dark areas are identified as characters that need to be recognized and the light areas as background.</p> <p>The dark areas are then processed further to find alphabetic letters or numeric digits. OCR programs can vary in their techniques, but typically involve targeting one character, word or block of text at a time. Characters are then identified using one of two <a href="https://www.techtarget.com/whatis/definition/algorithm">algorithms</a>:</p> <ol class="default-list"> <li><b>Pattern recognition</b>. OCR programs are fed examples of text in various <a href="https://www.techtarget.com/whatis/definition/font">fonts</a> and formats, which they then use <a href="https://www.techtarget.com/whatis/definition/pattern-recognition">pattern recognition</a> to compare and recognize characters in the scanned document.</li> <li><b>Feature detection</b>. OCR programs apply rules regarding the features of a specific letter or number to recognize characters in the scanned document. Features could include the number of angled lines, crossed lines or curves in a character for comparison. For example, the capital letter "A" may be stored as two diagonal lines that meet with a horizontal line across the middle.</li> </ol> <p>When a character is identified, it is converted into <a href="https://www.techtarget.com/whatis/definition/ASCII-American-Standard-Code-for-Information-Interchange">ASCII</a> code that computer systems can use to handle further manipulations. Users should correct basic errors, proofread and ensure that complex layouts are handled properly before saving the document for future use.</p> <figure class="main-article-image full-col" data-img-fullsize="https://www.techtarget.com/rms/onlineimages/how_optical_character_recognition_works-f.png"> <img data-src="https://www.techtarget.com/rms/onlineimages/how_optical_character_recognition_works-f_mobile.png" class="lazy" data-srcset="https://www.techtarget.com/rms/onlineimages/how_optical_character_recognition_works-f_mobile.png 960w,https://www.techtarget.com/rms/onlineimages/how_optical_character_recognition_works-f.png 1280w" alt="Diagram of how optical character recognition works." height="308" width="560"> <figcaption> <i class="icon pictures" data-icon="z"></i>Optical character recognition uses technology to convert documents into machine-readable text. </figcaption> <div class="main-article-image-enlarge"> <i class="icon" data-icon="w"></i> </div> </figure> </section> <section class="section main-article-chapter" data-menu-title="Optical character recognition use cases"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Optical character recognition use cases</h2> <p>OCR can be used for a variety of applications, including the following:</p> <ul class="default-list"> <li>Scanning printed documents into versions that can be edited with word processors, like Microsoft Word or <a href="https://www.techtarget.com/whatis/definition/Google-Docs">Google Docs</a>.</li> <li>Indexing print material for <a href="https://www.techtarget.com/whatis/definition/search-engine">search engines</a>.</li> <li><a href="https://www.techtarget.com/searchdatamanagement/feature/The-enterprise-advantages-of-automated-data-collection">Automating data entry</a>, extraction and processing.</li> <li>Deciphering documents into text that can be read aloud to visually impaired or blind users.</li> <li>Archiving historic information, such as newspapers, magazines or phonebooks, into searchable formats.</li> <li>Electronically depositing checks without the need for a bank teller.</li> <li>Placing important, signed legal documents into an electronic <a href="https://www.techtarget.com/searchdatamanagement/definition/database">database</a>.</li> <li>Recognizing text, such as license plates, with a camera or software.</li> <li>Sorting letters for mail delivery.</li> <li>Translating words within an image into a specified language.</li> </ul> </section> <section class="section main-article-chapter" data-menu-title="Benefits of optical character recognition"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Benefits of optical character recognition</h2> <p>The main advantages of OCR technology are the following:</p> <ul class="default-list"> <li>saves time;</li> <li>decreases errors;</li> <li>minimizes effort; and</li> <li>enables actions that are not possible with physical copies, such as <a href="https://www.techtarget.com/searchstorage/definition/compression">compressing</a> into ZIP files, highlighting keywords, incorporating into a website and attaching to an email.</li> </ul> <p>While taking images of documents enables them to be digitally archived, OCR provides the added functionality for editing and searching those documents.</p> <div class="youtube-iframe-container"> <iframe id="ytplayer-0" src="https://www.youtube.com/embed/Q5U_VEmcY-M?autoplay=0&modestbranding=1&rel=0&widget_referrer=null&enablejsapi=1&origin=https://www.techtarget.com" type="text/html" height="360" width="640" frameborder="0" loading="lazy"></iframe> </div> <p><i>OCR pulls text from images, but intelligent document processing (IDP) goes further—understanding meaning and context. Discover the key </i><a href="https://www.techtarget.cidzfom/searchcontentmanagement/feature/OCR-vs-IDP-Whats-the-difference"><i>differences between OCR vs. IDP</i></a><i> and why they matter.</i></p> </section> OCR (optical character recognition) is the use of technology to distinguish printed or handwritten text characters inside digital images of physical documents, such as a scanned paper document. https://cdn.ttgtmedia.com/visuals/digdeeper/4.jpg https://www.techtarget.com/searchcontentmanagement/definition/OCR-optical-character-recognition Tue, 09 Sep 2025 12:58:00 GMT What is OCR (optical character recognition)? WhatIs 60 webmaster@techtarget.com