The growing adoption of cloud-based network analytics solutions is an emerging trend in the network analytics industry. Organizations are increasingly migrating their network analytics to the cloud to leverage the benefits of scalability, flexibility, and cost-effectiveness. Cloud-based solutions allow real-time analysis of network data from any location, making it easier for businesses to monitor and manage their networks remotely.
For instance, in October 2021, Ericsson launched the Network Data Analytics Function (NWDAF) for cloud-native 5G Core. It helps operators optimize their 5G networks, ensuring efficient and reliable connectivity for various services and applications, including IoT and high-speed data transfer. This trend also facilitates the integration of Artificial Intelligence (AI) and Machine Learning (ML) for more advanced analytics and predictive insights, fueling the demand for cloud-based network analytics solutions.
The integration of AI and ML is another growing trend in the network optimization market. AI and ML technologies are being utilized to enhance network performance, efficiency, and security. These advanced algorithms can analyze large volumes of network data in real time, identifying patterns and anomalies that human operators might miss. This enables proactive network optimization, predictive maintenance, and automated response to security threats, ultimately leading to improved network reliability and performance. AI & ML integration is poised to revolutionize network optimization practices in the coming years.