Healthcare · Azure Data Warehouse · Power BI · Multi-Site Analytics
Data spread across multiple practice management systems with no unified warehouse for cross-clinic reporting.
Clinical leaders lacked a unified view of network performance, patient volumes, and financial metrics.
Time-consuming, error-prone manual data extraction replaced the need for automated dashboard delivery.
Inconsistent data quality and no row-level security limited self-serve analytics across the network.
Phase 1: ETL to Azure; Phase 2: Azure Data Lake & DWH with quality checks; Phase 3: Power BI dashboards with RLS.
Power BI dashboards with Python scripting deployed for clinic and network performance monitoring.
Business logic, performance optimization, and quality frameworks ensuring ongoing accuracy and reliability.
Row-level security enabling safe self-serve analytics across the hospital network for all roles.
All practice management systems in one Azure warehouse.
KPI dashboards across the hospital network.
Robust data quality and business logic frameworks.
Row-level security enabling independent analytics.