Best Power BI Architecture for Multiple Reports with Dynamic RLS and Different Refresh Frequencies

Scenario:

• Need to build 3 Power BI reports that share common dimensions (Geo, User mapping) but have different fact tables.

• One report has a very large dataset and requires bi-monthly refresh.

• Two reports require daily refresh.

Security Requirements:

• User Group A (restricted users) → RLS based on USERPRINCIPALNAME, limited to their assigned geography.

• User Group B (central users) → should select a user from Group A via a slicer and view data in that user’s security context.

• Slicer behavior and security need to be consistent across all reports.

Architecture Challenge:

• Single semantic model:

  • ✅ Easier to implement shared RLS and synced slicers

  • ❌ Hard to manage different refresh frequencies and performance for large datasets

• Multiple semantic models:

  • ✅ Easier refresh management

  • ❌ RLS does not flow across models

  • ❌ Slicers cannot be synced across models

Scalability Requirement:

• Frequent enhancements and new fact tables are expected.

• Want to avoid maintaining multiple copies of reports/models, to reduce complexity and maintenance overhead.

Question:
What is the recommended Power BI architecture or modeling strategy to support:

• Shared dimensions and security logic

• Dynamic RLS for User Group B

• Different refresh frequencies for large and small fact tables

• Scalable design without duplicating reports or models

• Consistent slicer behavior across all reports