The integration of identity analytics solutions within existing security infrastructure and systems is a complex process that requires significant time, money and effort from organizations. These solutions need to be seamlessly integrated with directories, directories, applications, databases and other identity platforms that may have been in use for several years. Any mismatches or errors during integration can compromise security and privacy. Ensuring proper system integration across different internal departments and technologies is a huge challenge for many firms. The costs of hiring skilled integration experts and opportunity costs of deployment during integration can be very high. This level of investment deters many small and medium enterprises from adopting identity analytics solutions.
Additionally, maintaining identity analytics solutions and keeping them updated with the latest technologies also places a considerable cost burden on organizations. Authentication and authorization mechanisms keep evolving with new threats emerging every day. Solution providers need to regularly release updates to patch vulnerabilities, add new features and optimize performance. Analyzing tremendous volumes of identity data on an ongoing basis also requires high computing power and data storage capacities. All of these ongoing maintenance activities involve recurring license fees, support contracts, infrastructure investments and manpower costs.
Market Opportunities: Emergence of IoT and connectivity of devices
The emergence of the Internet of Things (IoT) and increased connectivity of devices is poised to be a great opportunity for the global identity analytics market. As more "things" and devices become connected to the internet, from home appliances to industrial machinery to transportation and more, each one will need a unique digital identity to function securely and interact with other systems. This massive growth in the number of connected "identities" will drive tremendous demand for identity analytics technologies and solutions.
Furthermore, the complex requirements of handling IoT identity analytics - including the episodic and incomplete nature of sensor data, distributed and edge-based processing models as well as strict regulations around privacy and security in some verticals - demand highly sophisticated and specialized capabilities from vendors. This specialized nature of IoT use cases represents a substantial greenfield opportunity for focused identity analytics providers to establish beachheads and tailor their platforms for the IoT era. Given the projected explosive growth of IoT networks and the value that can be unlocked through identity-driven insights, it is likely to significantly expand the contours of the global identity analytics market in the coming years.
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