Skip to main content

Row-Level Security (RLS) vs Object-Level Security (OLS) in Power BI

Row-Level Security (RLS) vs Object-Level Security (OLS) in Power BI




Power BI provides robust security features that allow organizations to control data access at various levels. Two key mechanisms for securing data in Power BI are Row-Level Security (RLS) and Object-Level Security (OLS).


1. Row-Level Security (RLS)


What is RLS? RLS restricts access to data at the row level based on user roles. This ensures that users see only the data they are authorized to view without creating multiple reports for different audiences.


Implementing RLS in Power BI


🔹 Static RLS – Manually assign user roles and filter specific data.

🔹 Dynamic RLS – Uses a security table with usernames mapped to their respective access levels.


Steps to Set Up RLS in Power BI Desktop


  1. Create Roles: In Modeling → Manage Roles, define filtering conditions using DAX expressions. Example:
  2. Assign Users: In the Power BI Service, assign users to the created roles.
  3. Test Security: Use View as Role to verify if access is properly restricted.

Use Cases of RLS


✅ Restrict sales data by region (e.g., Sales Managers see only their regions).

✅ Show employee records only to relevant department heads.

✅ Limit financial data access based on user roles (e.g., Executives vs. Staff).


2. Object-Level Security (OLS)


What is OLS? OLS restricts access to specific tables and columns in Power BI datasets. Unlike RLS, which filters data within tables, OLS completely hides tables/columns from unauthorized users.


Implementing OLS in Power BI


  1. Use Tabular Editor: OLS settings are configured using Tabular Editor (not directly in Power BI Desktop).
  2. Set Permissions: Define Read or None access on specific tables/columns.
  3. Deploy & Assign Roles: Apply the OLS configuration to your dataset in Power BI Service.

Use Cases of OLS


✅ Hide sensitive salary columns from general employees.

✅ Restrict financial data tables for non-finance personnel.

✅ Prevent access to confidential business KPIs while allowing general reporting.

Comments

Popular posts from this blog

Connecting Power BI to Azure Data Lake: Streamlining Big Data Analytics

Connecting Power BI to Azure Data Lake: Streamlining Big Data Analytics Azure Data Lake and Power BI provide a powerful combination for businesses to handle and analyze large datasets efficiently. Here’s a step-by-step breakdown of how connecting Power BI to Azure Data Lake helps streamline big data analytics. 1. What is Azure Data Lake? Azure Data Lake is a cloud-based storage solution designed to handle large volumes of structured and unstructured data. It provides highly scalable and cost-effective storage, making it an ideal choice for big data projects, data lakes, and large-scale analytics. 2. Benefits of Connecting Power BI to Azure Data Lake Handling Large Datasets : Power BI’s integration with Azure Data Lake allows users to work with large datasets without needing to import all the data into Power BI. Instead, users can connect and query data directly. Scalable Analytics : Azure Data Lake’s ability to scale horizontally ensures that it can handle growing volumes of data se...

Leveraging Power BI's Bookmarks and Selections for Interactive Dashboards

Leveraging Power BI's Bookmarks and Selections for Interactive Dashboards Bookmarks and Selections in Power BI are powerful features that can significantly enhance the interactivity and user experience of dashboards. Here's how you can use them effectively: 1. What are Bookmarks in Power BI? Bookmarks capture the current state of a report page, including: Visible or hidden visuals Filter states Slicer selections Sort order, drill state, and focus mode By saving different views of your report with bookmarks, you can create interactive storytelling, custom navigation, and dynamic reports. 2. What is the Selection Pane? The Selection Pane lets you control the visibility of report visuals. Using the pane, you can: Show or hide visuals based on user actions Layer visuals in an orderly manner to control how users interact with them Combine with bookmarks to toggle the visibility of different report components 3. Use Cases for Bookmarks and Selections Here are some common scenarios ...

Integrating Grafana with Power BI: A Step-by-Step Guide

Integrating Grafana with Power BI: A Step-by-Step Guide Data visualization tools like Power BI and Grafana are popular for their unique capabilities but combining them can enhance your analytics capabilities. Here's how you can integrate Grafana with Power BI to leverage the best of both tools. Why Integrate Grafana and Power BI? Comprehensive Analysis : Power BI excels at business analytics, while Grafana shines in real-time monitoring and system metrics. Enhanced Insights : Integrating these tools helps consolidate diverse data sources for a unified view. Custom Dashboards : Combine Power BI's visuals with Grafana's real-time alerting capabilities. Pre-Requisites A working Grafana instance. Power BI data source or reports available for integration. Necessary permissions for both tools. Grafana plugins like the Power BI REST API or third-party connectors. Step-by-Step Integration Step 1: Set Up Power BI API Access Go to the Power BI Service . Navigate to Admin Portal >...