市场调查报告书
商品编码
1554249
身分分析市场规模、份额、成长分析:按组件、按服务、按部署、按组织规模、按应用程式、按行业、按地区 - 行业预测,2024-2031 年Identity Analytics Market Size, Share, Growth Analysis, By Component, By Services, By Deployment, By Organization Size, By Application, By Industry Vertical, By Region - Industry Forecast 2024-2031 |
2022年Identity Analytics的全球市场规模将为206.7亿美元,预测期间(2024-2031年)复合年增长率为4.4%,从2023年的215.8亿美元增至2031年的304.5亿美元,预计还会增长。
身分分析市场旨在解决与身分和存取管理相关的日益增长的挑战。随着网路威胁和资料外洩变得越来越普遍,企业需要有效的解决方案来验证和管理使用者身分、遵守法规并保护敏感资讯未授权存取。云端运算和数位转型的采用正在推动身分分析市场的成长。此外,对即时监控、威胁侦测和身分管治解决方案不断增长的需求也为市场扩张创造了有利的环境。此外,银行、医疗保健和政府等部门也越来越认识到身分和存取管理的重要性,为供应商提供创新和全面的身份分析工具创造了机会。全球身分分析市场是由不断演变的网路威胁以及对先进解决方案来驾驭复杂IT基础设施的需求所推动的。儘管在整合和法规遵循方面面临挑战,但这为供应商提供了一个重要的机会来开发复杂的解决方案,以增强组织的安全性、提高业务效率并确保符合行业标准。
Global identity analytics market size was valued at USD 20.67 billion in 2022 and is poised to grow from USD 21.58 billion in 2023 to USD 30.45 billion by 2031, at a CAGR of 4.4% during the forecast period (2024-2031).
The identity analytics market aims to address the growing challenges related to identity and access management. As cyber threats and data breaches become more frequent, organizations require effective solutions to authenticate and manage user identities, ensure regulatory compliance, and protect sensitive information from unauthorized access. The adoption of cloud computing and digital transformation initiatives has fueled the growth of the identity analytics market. This market also benefits from increasing demand for real-time monitoring, threat detection, and identity governance solutions, which create a favorable environment for expansion. Additionally, rising awareness of the importance of identity and access management in sectors such as banking, healthcare, and government presents opportunities for vendors to deliver innovative and comprehensive identity analytics tools. The global identity analytics market is driven by the need for advanced solutions to navigate evolving cyber threats and complex IT infrastructures. Despite challenges related to integration and regulatory compliance, the market offers significant opportunities for vendors to develop sophisticated solutions that enhance organizational security, improve operational efficiency, and ensure compliance with industry standards.
Top-down and bottom-up approaches were used to estimate and validate the size of the Global Identity Analytics market and to estimate the size of various other dependent submarkets. The research methodology used to estimate the market size includes the following details: The key players in the market were identified through secondary research, and their market shares in the respective regions were determined through primary and secondary research. This entire procedure includes the study of the annual and financial reports of the top market players and extensive interviews for key insights from industry leaders such as CEOs, VPs, directors, and marketing executives. All percentage shares split, and breakdowns were determined using secondary sources and verified through Primary sources. All possible parameters that affect the markets covered in this research study have been accounted for, viewed in extensive detail, verified through primary research, and analyzed to get the final quantitative and qualitative data.
Global Identity Analytics Market Segmental Analysis
The global identity analytics market is segmented based on component, services, deployment, organization size, application, industry vertical, and region. In terms of component, the market is segmented into Solutions and Services. Based on services, the market is segmented into Professional Services, and Managed Services. Based on deployment, the market is segmented into on-Premises, and cloud. Based on organization size, the market is segmented into Small and Medium-Sized Enterprises, and Large Enterprises. Based on application, the market is segmented into Account Management, Customer Management, Fraud Detection, GRC Management, Identity and Access Management, and Others. Based on industry vertical, the market is segmented into BFSI, Government and Defense, IT and Telecom, Energy and Utilities, Manufacturing, Retail, Healthcare, Others. By region, the market is segmented into North America, Europe, Asia Pacific, Middle East and Africa, and Latin America.
Drivers of the Global Identity Analytics Market
As of 2023, the adoption of the Zero Trust security framework has gained significant momentum across organizations. This approach focuses on continuously verifying and validating every user and device before allowing access to resources, regardless of their location. Advanced identity analytics solutions play a crucial role in monitoring user behavior, analyzing access patterns, and identifying real-time anomalies. The rising complexity of cyber threats, coupled with the need for stronger authentication and access controls, has accelerated the adoption of the Zero Trust model. As a result, there is growing demand for identity analytics tools that provide granular visibility and actionable insights into user activities, enabling organizations to strengthen their security posture and implement robust protection strategies more effectively.
Restraints in the Global Identity Analytics Market
Despite the rising demand for identity analytics solutions, organizations face ongoing challenges around data privacy and security. The collection and analysis of sensitive identity-related information heighten concerns about potential data breaches and unauthorized access. To safeguard privacy and meet data protection regulations, organizations must implement stringent security measures, including advanced encryption, secure data storage, and adherence to industry best practices. Ensuring these protections requires significant investment and careful planning, which can create obstacles to the widespread adoption of identity analytics solutions. Balancing the need for effective identity management with privacy concerns remains a key challenge for organizations.
Market Trends of the Global Identity Analytics Market
As of 2023, Artificial Intelligence (AI) and Machine Learning (ML) remain crucial in transforming the identity analytics market. AI-powered identity analytics solutions have become essential for processing vast amounts of identity data, identifying patterns, and detecting anomalies or suspicious activities in real-time. Machine learning algorithms continuously improve by learning from user behavior, allowing them to adapt to evolving threats and enhance the accuracy of identity analytics. This integration of AI and ML into identity analytics has led to more precise and efficient identity risk management strategies. It enables organizations to proactively mitigate identity-based risks, such as insider threats and unauthorized access, strengthening overall security.