Use DATA to predict the future

Predictive analytics is seen by many as offering the potential to allow CSPs to make more accurate investments and to better tune their networks. If CSPs can forecast when and where problems might occur, they can implement predictive maintenance programmes to take action to prevent issues having any negative impact on networks, services or subscribers. Similarly, forecasting traffic growth and pinpointing it to specific areas of their networks can allow CSPs to direct their investments more effectively and secure better returns. Machine learning allows this process to be automated by leveraging artificial intelligence engines.

To achieve this, CSPs need to make more effective use of data. While CSPs have a vast source of data available, they need to be able to collect and format the data, so that it can be processed by analytics engines. Before reliable, accurate predictions can be made, a consistent supply of high-quality data must be obtained.