Big Data Cases Telecommunications

Top Six Telecommunications Big Data Use Cases

Explore How Big Data Analytics Can Transform Operations, Enhance Customer Experiences, and Boost the Bottom Line.

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About the Top Six Telecommunications Big Data Use Cases Ebook

For telecommunications firms, which now include cable and satellite TV companies, driving profitable growth in today’s markets is no small feat. Regulation is intensifying. Internet access is practically ubiquitous in those markets. With most markets mature, competition is fierce, especially as OTTs move into core sources of revenue. And although customer acquisition costs are high and margins are slim, capital costs are skyrocketing.

Industry leaders have already begun planning for – and even investing in – new technologies that will set the new standards for network quality, customer experience, and the agility needed to deliver new services. Investment in these new technologies means new data points and sources, expanding data volumes, and huge potential for data-driven differentiation amongst competing telcos.

Exploring Use Cases for Telecom Providers

Six use cases in production to gain a competitive advantage.

DataOps Process: Data Platform Capabilities

Harnessing Big Data as a Strategic Asset

Armed with an understanding of the potential in these use cases, the next logical question is – how does all of this work in practice?

Unlocking the Power of Big Data

Integration. Preparation and analytics. Visualization. Operationalization.

Getting Started

Datameer can vastly accelerate your time to insights about customers, offerings, operations, and investments.


Given the growing demand for high-definition television (HDTV), there’s an opportunity to understand customer behavior within different viewing segments and identify the most successful channels for their future HDTV offerings. The insights gained can create specific HDTV packages designed to be marketed to specific target segments.

Using big data analytics, carriers can easily collect, aggregate, and analyze all of their channel stream data from set-top-boxes, visualize the results to predict the most successful segments for HDTV viewing accurately, and create optimal new product packages based on the results.


Consider cases where customers are paying more for HDTV content services. In exchange for higher costs, they expect their service provider to deliver a consistent, high-quality viewing experience, even during periods of peak demand. But for many telecom providers, measuring the quality of experience (QoE) is a difficult and data-intensive activity, as is detecting exactly where issues occur on their network so they can be fixed quickly. To gain this level of transparency, carriers need a way to integrate the vast amounts of structured and unstructured data points for the end-user customer experience and build a comprehensive, accurate picture.

Using big data analytics, carriers can aggregate data on billions of video sessions and analyze it in minutes to reveal content delivery network (CDN) performance.

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