Data Analytics
for Telecommunications

Network analytics can be integrated with OSS/BSS systems. This integration is crucial for eliminating data silos and closed-loop automation. Benefits include enhanced customer experience, automated services, monetization opportunities and lower customer churn rates.

Network analytics empowers telecommunications operators to be proactive in identifying and addressing warning signs. Practical use cases include predictive maintenance of network equipment (routers, switches, towers), real-time anomaly detection (lower quality of signal, traffic surges), automated root cause analysis and real-time traffic management.

Network analytics help to improve network performance and reliability by monitoring real-time traffic, adjusting resources, deploying predictive maintenance and supporting strategic planning.

Telco data analytics help to reduce customer churn by identifying red flags like drops in usage, complaints and negative interactions. Retention teams are notified so that attempts can be made to rectify the situation and ensure a dissatisfied customer does not resign.

Telecom providers use data analytics for geospatial site selection of new cell towers, cost modeling, revenue projections, broadband mapping, real-time network issues like traffic loads, self-optimizing networks and bandwidth management. Data analytics is also critical for predictive maintenance initiatives and energy savings (identifying underused equipment).

Network analytics enables operators to create multiple virtual networks (slices) on a single piece of infrastructure. Network analytics supports 5G launches and deployments, increases security measures and delivers increased standardization through network data analytics function (NWDAF).

Tools can be divided into several large categories, of which there are many commercially available options. Categories include cloud and data platforms, OSS/BSS tools, Business Intelligence, as well as data streaming and orchestration.