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 AdfarTech 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 AdfarTech 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
