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Healthcare

Healthcare Provider Optimizes Patient Analytics with Power BI and Fabric

A healthcare provider needed real-time patient and operational analytics. We replaced Tableau extracts with a Fabric-backed Power BI DirectQuery solution and achieved near real-time reporting with proper governance.

Regional healthcare provider (anonymized)Healthcare4 months
Key outcome

Real-time Reporting

The challenge

The client had built a large Tableau environment on extracts that refreshed nightly. Clinicians and operations needed more current data for bed management, length-of-stay, and capacity planning. Extracts were heavy to maintain and did not support real-time decisions. Security and audit requirements demanded row-level security and clear lineage.

  • Nightly Tableau extracts; no real-time visibility
  • Heavy extract refresh and maintenance
  • Need for row-level security and audit trail
  • Desire to align with existing Microsoft identity and compliance

Architecture: from extracts to DirectQuery

We designed a Fabric-based architecture: source systems feed a medallion layer in OneLake; a Gold semantic layer is exposed via DirectQuery to Power BI. Power BI reports use that semantic model so users get near real-time data without moving full extracts. RLS is applied at the model so users only see data they are allowed to see.

Data flows from source systems through Fabric medallion layers to Power BI DirectQuery.

Security and governance

We implemented row-level security so clinicians see only their units or facilities, and administrators see aggregated views where permitted. Sensitivity labels and audit logging were configured. The move to Power BI and Fabric allowed the client to leverage Azure AD and Microsoft Purview for identity and compliance.

RLS filters data by user/role; audit logging tracks access.

Key outcomes

The client now has real-time patient and operational analytics in Power BI, with no overnight extract jobs. Governance and security meet their compliance requirements, and the team can iterate on reports without managing Tableau extract schedules.

Near real-time
Data freshness
Eliminated
Extract maintenance
In place
RLS & audit
4 months
Timeline

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