Data-driven differentiation

Shanthi Ravindran and Justin van der Lande
26 Mar 2015

Big data and analytics software solutions are becoming, and will continue to be, a critical part of every operator’s systems architecture. Deploying analytics software offers CSPs the opportunity to generate valuable insights from big data, enabling them to improve internal operations and generate additional revenue.

CSPs possess immense amounts of data on each of their subscribers. This includes internal information associated with their profile, their data records (xDRs), location information, network usage data and interactions with external companies including on social media. Every call made, message sent, app used or website visited is added to the understanding of each subscriber and the volume of this data continues to grow in size. Analysys Mason forecasts the worldwide analytics software market for telecoms service providers to grow from $2.1 billion in 2013 to $3.8 billion in 2018, at a 12.9% compound annual growth rate (CAGR).

The transformation of established data warehouses into supporting big data solutions, as championed by Hadoop-based solutions, is already underway. Big data solutions are enabling the building of cost-effective “data lakes”, which can be utilized for in-depth analytics. A data lake can be defined as a massive data repository for storing big data in its original format. Having a framework that can support real-time and off line requirements means that CSPs’ business requirements will not be limited by their infrastructure.

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