Row-Level Security (RLS) in Power BI provides a way to restrict data access for specific users based on filters applied to the data model. Here's how RLS interacts with the Power Pivot model:
1. RLS in Power Pivot Model:
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Integration with Power Pivot: RLS is applied to the Power Pivot model through DAX filters. It allows you to define roles and filters in the data model to control which data a user can see based on their login.
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User Access Control: You can define roles in Power BI Desktop that specify what data is visible to different users. These roles are tied to tables and columns in your Power Pivot model and can restrict access based on user-specific criteria (e.g., geographic region, department).
2. Data Restrictions:
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Context-Sensitive Filtering: RLS can filter rows based on user attributes, ensuring that users only see data relevant to them. For example, a salesperson in one region will only see data for their specific region in the report.
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Dynamic Filtering: RLS can be dynamic, meaning it can change based on the user who is logged in. This helps maintain the security of sensitive data across different user groups.
3. Impact on Governance and Quality Assurance:
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Ensuring Data Security: RLS helps enforce data governance by ensuring that users can only view data that they are authorized to see, ensuring compliance with data privacy regulations.
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Consistency and Quality Assurance: With RLS applied, the same report can be distributed to different users while ensuring consistent data visibility rules, enhancing quality assurance during report deployment.
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Testing and Validation: Before deploying reports, it's crucial to test RLS settings to ensure that data access is correctly restricted according to the defined roles, preventing unauthorized data exposure.
