As telecommunications operators collect more data through fully digitized, end-to-end processes, they must adopt the playbook of the hyperscalers and innovate with data to fully capitalize on 5G opportunity. As a result, the BSS data warehouses that they depend on for financial and marketing analytics are under more stress than ever before. Several key reasons include:
- Subscriber growth leading to more CDR data
- Migration to 5G results in more GPRS sessions, further increasing CDR volume
- Increased use of data analytics by more departments
When coupled with state-of-the-art analytics technologies, such as machine learning and robotic process automation (RPA), telecommunication operators are limited only by their imagination and the constraints of their analytics environment.
Most telcos run legacy data warehouse platforms, sometimes nearing the end of their lives. Upgrading these legacy on-prem data warehouses by adding new storage capacity to deal with the increased data volumes requires “forklift upgrades.” Adding necessary compute capacity to address the analytics demands from more users and data is expensive. These legacy data warehouses cost too much to expand because they lack the elasticity provided by modern data warehouses and don’t provide a clear path to the cloud. As a result, they fail to deliver on financial needs, resulting in suboptimal payments, poorly targeted marketing, unhappy users, and SLA breaches.
Moving to the cloud in one shot is a massive, costly business risk that exposes the operator to an unpredictable, consumption-based business model which disincentivizes further use of analytics, and risk of being locked into a cloud platform. Some operators have experimented with Hadoop as a cost-effective solution to growth but the inherent complexity and hidden running costs mean this has largely failed to deliver on its promise.