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).

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