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Based on enterprise size, the large enterprises segment held over 63% of the network analytics market share in 2022. Large organizations are increasingly adopting network analytics solutions to gain better visibility into their complex and sprawling networks. These solutions help them monitor network performance, detect anomalies, and ensure optimal resource allocation. These enterprises often deal with higher security risks, making advanced analytics crucial for threat detection and mitigation. As a result, they are investing in sophisticated network analytics tools to enhance network efficiency, security, and overall operations.
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Based on the application, the Network Performance Management (NPM) segment accounted for 31% of the network analytics market share in 2022. With the increasing complexity of networks and the importance of maintaining optimal performance, organizations are turning to NPM solutions. These tools offer real-time monitoring, analysis, and troubleshooting capabilities, ensuring that networks operate smoothly and efficiently. As businesses rely more on digital operations, NPM becomes indispensable for delivering a seamless user experience and meeting performance expectations, boosting its adoption significantly in the market.
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North America network analytics market recorded more than 34% of revenue share in 2022. The region's large concentration of tech-savvy enterprises is driving the adoption of advanced network analytics solutions to enhance their IT infrastructure performance and security. Increasing cyber threats and stringent regulatory requirements are pushing organizations to invest in comprehensive network analytics tools. The rapid expansion of cloud computing and data center facilities in North America further fuels the demand for network analytics to ensure optimal network operations and cybersecurity measures.
For instance, in October 2022, Oracle introduced the Oracle Network Analytics Suite, a cloud-native collection of analytics tools. It merges network function data with AI and ML to empower operators with data-driven insights and automated decisions for optimizing the performance and stability of their 5G network core, ensuring enhanced network efficiency and reliability. These combined factors contribute to substantial growth in the region.