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

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

Solution Overview
Foundational Data Lake setup using PaaS services on MS Azure 
Data science modeling 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 analyzed
Rapid on-boarding of template-driven approach, Data Standardization, Cleansing, Validation & Auto-profiling framework using Coforge’s proprietary Accelerator
Governance UI for Metadata Search, Lineage analysis, Manage objects, Analyze Profiling Statistics, and Perform Operational Reporting.
Call drop prediction capabilities provided via MLXpress

Data analyzed from the research helped the client in policymaking
Enabled Mobile and broadband service assessment across multiple dimensions - service providers, technology, geo, data/voice



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