All networks need proper monitoring and management. Sophisticated processes are required to drill-down into a network, find the causes of problems and discover ways to prevent them. Similar processes are essential to analyze the effects of any issues that do arise, and to implement damage limitation and solutions.
Analysis of high-quality data makes these processes possible. With the number of devices connected and communicating within the Internet of Things, and the high-speed, high-bandwidth possibilities of 5G, traditional data collection and analysis is no longer sufficient to ensure such quality, so telecommunications network operators are turning to artificial intelligence and machine learning to help them.
AI enhances baselines by using many prediction models to establish the probability that a given parameter will be reached or exceeded. The process is stronger when ML is deployed for anomaly detection. Once detected, the system can identify the original cause of an anomaly, and group similar events together, even if a single root cause is responsible for many symptoms. From the business perspective, this means automated monitoring for customer-focused issues such as KPIs and SLAs, using data direct from the system.
With the data in place, products such as Comarch Artificial Intelligence (AI) Control Desk simplify and optimize the network management process for telecommunications operators. Such products will be essential sooner rather than later, as we’re rapidly moving towards a point when networks (and the data they receive and generate) will be so complex that monitoring and maintenance will only be possible using automated systems.