Data Analytics using Microsoft Fabric

Prior to engaging Saints & Masters, field engineers had to manually cross-reference three disconnected systems — SQL Server, PostgreSQL, and Dataverse — before every service call. This fragmented lookup process created several compounding operational inefficiencies:

• •3 Disconnected Systems: SQL Server (archived history), PostgreSQL (ops & log data), and Dataverse (CRM & tickets) operated as fully siloed environments with no integration or shared data layer.
• •Slow Response Times: Engineers spent significant pre-visit time piecing together customer context from multiple sources, delaying service response and reducing productivity.
• •Low First-Time Fix Rates: Incomplete asset visibility meant engineers often arrived on-site without the full picture — missing service history, open tickets, or asset configurations — requiring costly repeat visits.

Saints & Masters designed and deployed a Microsoft Fabric-based lakehouse architecture using a Medallion (Bronze → Silver → Gold) data model, with three distinct ingestion strategies tailored to each source system:

• •SQL Server → OneLake: Full historical load of archived service records via Azure Data Factory into Fabric Lakehouse Bronze → Silver → Gold layers using Spark.
• •PostgreSQL → OneLake: Watermark-based incremental CDC ingestion of live operational data and engineer activity logs into OneLake.
• •Dataverse Shortcuts (Zero-Copy): CRM records and service tickets exposed virtually in Lakehouse — no data moved, governance fully intact. Data stays in Dataverse via OneLake.
• •Medallion Architecture: Standardised entity model: Customer → Asset → Service History, powering a unified Power BI dashboard.

The Microsoft Fabric implementation delivered measurable operational improvements across field service operations:

• •3 Source Systems Unified: Transition from three siloed databases to a single lakehouse with a standardised entity model spanning customers, assets, and service history.
• •1 Unified Power BI Dashboard: Move from multi-system lookups to a single pane of glass providing complete customer asset history and open service tickets.
• •Faster Diagnosis: Complete customer asset history and open service tickets available in a single Power BI view — eliminating the need for engineers to cross-reference multiple systems before every call.
• •Higher First-Time Fix Rate: Engineers arrive on-site fully informed with asset context, service history, and open tickets — reducing repeat visits and associated costs.
• •Better Customer Experience: Efficient, personalised service delivery powered by real-time unified data — improving satisfaction and trust.