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Mobile network analytics on Azure data lake for a European telecom regulator

Problem Statement

  • Ingest large volume (multi-TB/week) of mobile and broadband usage data from a third-party service provider.
  • Perform market research on full datasets (instead of samples).

Solution Overview

  • Foundational Data Lake setup using PaaS services on MS Azure
  • Data science modelling was deployed using python to predict the call drops on Azure data lake.
  • Ingestion of multi-TB data / week from 3rd party source (P3)
  • 3 billion data points from 150,000 mobile devices analysed.
  • Rapid on-boarding of template driven approach, Data Standardization, Cleansing, Validation & Auto-profiling framework using our Accelerator.
  • Governance UI for Metadata Search, Lineage analysis, manage objects, analyze profiling statistics and perform operational reporting.


  • Data analyzed from the research helped client in policy making
  • Mobile and broadband service assessment across multiple dimensions - service providers, technology, geo, data/voice
  • Call drop prediction capabilities provided via MLXpress

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