Data Modernization through Customer Analytics for a Leading Retailer in US

Problem Statement

The customer wanted to build a future-proof Azure based Data platform to mitigate some of their existing challenges & enable nextgen capabilities with a core objective of driving intelligent business decisions through analytics. In the process they also wanted to improve efficiency & standardization, incorporate best practices &optimize costs. Some of the key focus areas included pricing excellence, increasing new sales & customer retention.

Solution Overview

• Conducted current state assessment of existing data landscape to identify challenges and understand desired capabilities and gaps
• Proposed a nextgen target state Azure Data Lake solution
• Implemented Customer Analytics and a Cross sell and up Sell model
• Defined roadmap for the data modernization and monetization journey
• Setup a scalable Azure data platform to ingest, manage, link and analyze all types of data in one place leveraging Coforge innovations
• Enabled advance analytics MVP for pricing excellence
• Enabled advance analytics MVP for pricing excellence
• Built a robust Data quality and Data Governance process

Outcomes

• Future state Data Lake architecture anchored on best practices and learnings from multiple engagements.
• ~ 30-40% faster time market for platform build by leveraging Coforge innovations “DLXpress” and “DQXpress”.
• Robust Data quality and Data Governance processes provided assurance and improved adoption of the platform.
• Use Case driven actionable roadmap to achieve incremental benefits.
• Prescribed POVs for best practices, standards, tool & cloud platform comparison and industry trends.

Current State Data Landscape

Target State Architecture