Row-level security (RLS) in Power BI restricts what data each user sees in a report. You define DAX roles that filter table rows based on user identity. RLS is required for HIPAA, SOC 2, and FINRA compliance. EPC Group implements enterprise RLS patterns for Fortune 500 organizations across healthcare, financial services, and government.
Key Facts
- RLS is configured in the semantic model — not in the report or dashboard.
- Static RLS: fixed roles with DAX filter expressions (e.g., [Region] = "West").
- Dynamic RLS: uses USERPRINCIPALNAME() to filter rows based on the logged-in user's email.
- Object-level security (OLS): hides entire columns or tables from specific roles.
- RLS applies in Power BI Service, embedded reports, and mobile apps.
- EPC Group: 29 years Microsoft consulting. 1,500+ Power BI deployments including regulated-industry RLS implementations.
Power BI And Row Level Security
Power BI Row-Level Security (RLS) Guide
Row-level security (RLS) in Power BI restricts what data each user sees in a report. You define DAX roles that filter table rows based on user identity. RLS is required for HIPAA, SOC 2, and FINRA compliance. EPC Group implements enterprise RLS patterns for Fortune 500 organizations across healthcare, financial services, and government.
Key facts
- RLS is configured in the semantic model — not in the report or dashboard.
- Static RLS: fixed roles with DAX filter expressions (e.g., [Region] = "West").
- Dynamic RLS: uses USERPRINCIPALNAME() to filter rows based on the logged-in user's email.
- Object-level security (OLS): hides entire columns or tables from specific roles.
- RLS applies in Power BI Service, embedded reports, and mobile apps.
- EPC Group: 29 years Microsoft consulting. 1,500+ Power BI deployments including regulated-industry RLS implementations.
Static RLS
Static RLS uses hardcoded DAX expressions to filter rows for a role. Best for fixed, predictable access patterns.
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Why Organizations Choose EPC Group
EPC Group is a Houston-based Microsoft consulting firm with 29 years of enterprise implementation experience and over 10,000 successful deployments across Power BI, Microsoft Fabric, SharePoint, Azure, Microsoft 365, and Copilot. We serve organizations across all industries including Fortune 500, federal agencies, healthcare, financial services, government, manufacturing, energy, education, retail, technology, and global enterprises.
What sets EPC Group apart is our governance-first approach. Every engagement begins with a security and compliance assessment. Our team of senior architects brings hands-on delivery experience across HIPAA, SOC 2, FedRAMP, and CMMC environments. We own outcomes, not hours.
- Fixed-fee accelerators with predictable pricing and defined deliverables
- Senior architect engagement on every project, not rotating juniors
- Compliance-native delivery for regulated industries
- End-to-end coverage from strategy through 24/7 managed services
- 11,000+ enterprise engagements refined into repeatable, risk-controlled patterns
Call (888) 381-9725 or email contact@epcgroup.net for a free assessment.
Power BI Strategy: 2026 Considerations for Power BI And Row Level Security
Power BI capacity sizing in 2026 starts with the F-SKU economics: F2 ($263/mo) covers small workloads with up to 4 GB of memory and roughly 30 reports, F4 ($526/mo) handles a typical mid-market deployment with semantic-model refresh windows under 10 minutes, and F64 ($5,257/mo) is the sweet spot for enterprises consuming Power BI alongside Microsoft Fabric data engineering, lakehouse storage, and real-time intelligence. Capacity right-sizing should be revisited every 90 days because Microsoft adjusts F-SKU memory allocations, paginated report performance, and Direct Lake mode availability with each major service update.
Direct Lake mode has changed the economics of enterprise Power BI in 2026: instead of importing data into Vertipaq, semantic models now query OneLake-resident Parquet files at near-Import-mode performance without the refresh-window cost. For a Fortune 500 finance organization migrating from a 30-minute Import-mode refresh, the equivalent Direct Lake model typically queries fact data in under 800 ms while removing the entire refresh-orchestration job from Azure Data Factory.
Decision factors EPC Group evaluates
- Capacity sizing decision (F2/F4/F64+) tied to peak concurrent users and refresh window
- Copilot grounding quality assessment of semantic-model metadata
- Direct Lake mode adoption for Fabric-resident semantic models
- License optimization audit (Pro vs Premium Per User vs F-SKU)
- Row-level security via service principal authentication
For a tailored read on this topic in your specific tenant, contact EPC Group at contact@epcgroup.net or +1 (888) 381-9725. Engagement options at /pricing.