Fabric Modernisation to Support Customer Churn Modelling

The challenge

Data was fragmented across multiple silos, limiting data quality, governance, and the organisation’s ability to perform reliable analytics or develop predictive models and AI use cases.

The approach

Rationalised the existing data model to remove redundancy and improve consistency. Re-ingested trusted, validated data sources into Microsoft Fabric. Rebuilt data pipelines using a Medallion architecture (Bronze, Silver, Gold). Established clear data lineage, governance, and documentation throughout the platform.

The outcome

Delivered a Fabric-native, governed data architecture with a clean semantic model and OneLake connectivity, enabling reliable churn analysis today and providing a robust, AI-ready foundation for future advanced analytics initiatives.