Exploring Power BI Row-Level security

Introduction

Controlling data access is crucial in any organization, and Row-Level Security (RLS) in Microsoft Fabric helps restrict data visibility based on user roles or attributes. However, understanding when to use Static vs. Dynamic RLS can be challenging. In this conversation, Amit is exploring RLS and seeks guidance from Sara on how to implement it in real-world scenarios. Sara explains how Static RLS works well for predefined access rules, while Dynamic RLS offers a scalable approach by filtering data dynamically based on user attributes. Through practical examples, Amit gains clarity on choosing the right approach for his project, ensuring secure and efficient data access.

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Knowledge Check

Question 1: A multinational company has a Sales dataset containing sales records for different countries. The company wants each country’s manager to see only their own country’s data. The security roles will not change frequently. Which RLS approach is the best fit?

A) No RLS is needed since all managers can see all data
B) Static RLS, as each manager’s access is predefined and does not change dynamically
C) Dynamic RLS, as access should be determined based on user attributes at login
D) Assign separate datasets for each country instead of using RLS

Question 2: A company has a Customer Support dashboard where support agents should only see tickets assigned to them. The dataset contains a User Table that maps agents to their respective tickets using their email ID. Which implementation method should be used?

A) Apply a filter where support_agent = ‘John Doe’ for each user
B) Use a User Table and filter data dynamically based on the logged-in user’s email
C) Create a separate dashboard for each agent
D) Assign each agent an admin role so they can filter their own data manually