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 policy-making Enabled Mobile and broadband service assessment across multiple dimensions - service providers, technology, geo, data/voice