Data security is a top priority for organizations in 2025, and Power BI’s Row-Level Security (RLS) ensures that only authorized users can access specific data. Whether you’re working on financial reports, sales dashboards, or HR analytics, RLS helps protect sensitive information by dynamically filtering data based on users’ roles.
In this guide, you’ll learn how to assign RLS in Power BI step by step, from setting up roles to testing and best practices for security optimization.
What is Row-Level Security (RLS) in Power BI?
Row-Level Security (RLS) is a feature in Power BI that restricts access to data at the row level. It enables organizations to control who can view what data based on predefined rules. Instead of creating separate reports for different users, you can use RLS to filter data dynamically, ensuring secure and efficient data management.
Why Use RLS in Power BI?
✅ Enhances Data Privacy – Restricts unauthorized data access.
✅ Improves Report Performance – Avoids duplicating datasets for different users.
✅ Simplifies Report Management – Maintains a single report with dynamic filtering.
✅ Ensures Compliance – Helps meet security and regulatory requirements (e.g., GDPR).
Step 1: Prepare Your Data Model for RLS
Before applying RLS, ensure your data model supports security filtering. Ideally, your dataset should have:
- A fact table containing transactional data (e.g., Sales, Orders, Employees).
- A dimension table containing user roles (e.g., Region, Department, Manager).
- A user mapping table to associate users with their assigned data access.
Step 2: Define Roles in Power BI Desktop
1️⃣ Open Power BI Desktop and load your dataset.
2️⃣ Click on Model View in the left panel.
3️⃣ Go to the Modeling tab and select Manage Roles.
4️⃣ Click Create a New Role and enter a role name (e.g., “Regional Sales”).
5️⃣ Select the user mapping table and enter a DAX filter expression to restrict data.
💡 Pro Tip: If your data model has multiple related tables, ensure proper relationships so that RLS filters apply correctly.
Step 3: Test Row-Level Security in Power BI Desktop
Before publishing, test if RLS works as expected.
1️⃣ Go to Modeling > View As Roles.
2️⃣ Select the role you created (e.g., “Regional Sales”).
3️⃣ Enter a test user email and click OK.
4️⃣ Verify that only the relevant data is displayed for the selected user.
💡 New in 2025: Power BI now includes an AI-based Role Tester that suggests fixes for incorrect role setups.
Step 4: Assign Users to Roles in Power BI Service
Once the roles are created, you need to assign users in Power BI Service.
1️⃣ Publish your report to Power BI Service.
2️⃣ Navigate to Datasets > Security under your report.
3️⃣ Select the role you defined in Power BI Desktop.
4️⃣ Click Add Users and enter email addresses or security groups.
5️⃣ Click Save to apply changes.
💡 Best Practice: Instead of adding individual users, use Azure Active Directory Security Groups for easier role management.
Step 5: Verify Row-Level Security in Power BI Service
To confirm that RLS is working:
1️⃣ Open the Power BI Service and go to Dataset Settings.
2️⃣ Click on View As Role and select a user.
3️⃣ Verify that the data visibility matches the assigned role.
Best Practices for Implementing RLS in Power BI
✅ Use Dynamic RLS Instead of Static Roles
- Instead of defining multiple roles manually, use dynamic filtering with DAX expressions based on user logins.
✅ Optimize Data Relationships
- Ensure that tables have proper relationships so that filters apply across all datasets.
✅ Minimize Performance Issues
- Avoid complex DAX expressions that slow down report loading.
✅ Test Before Deployment
- Use Power BI Desktop’s “View As” feature and test with multiple users in Power BI Service.
✅ Combine RLS with Object-Level Security (OLS)
- Use Object-Level Security (OLS) to hide entire tables or columns, providing an extra layer of data security.
Common Mistakes to Avoid in RLS
❌ Forgetting to Apply RLS to All Related Tables – Ensure security rules apply across all relevant tables.
❌ Assigning Users Manually Instead of Using Security Groups – Use Azure AD groups for easier management.
❌ Not Testing RLS in Power BI Service – RLS can behave differently in the desktop and online versions, so always verify.
❌ Overcomplicating DAX Filters – Keep filtering logic simple for better performance.
Final Thoughts
Row-Level Security (RLS) in Power BI is an essential feature for managing secure and customized data access. By implementing dynamic RLS, leveraging Azure AD, and optimizing report performance, you can create highly secure and scalable Power BI dashboards.
