Power BI Row-Level Security
Wouldn’t it be nice if you could filter the rows a user sees in Power BI? What’s that? You’ve already implemented Row-Level Security at the database level? Well, that actually won’t help you in Power BI. Yikes. In this episode we discuss ways to filter by records in Power BI and why it might be so confusing to implement what at first glance seems like a straightforward request.
“Power BI Row-Level Security is completely different [than row-level security in SQL Server], uses the same exact name and is a source of confusion and frustration with customers.”
“When it comes to Power BI, you’ve got two types of row-level security that work and one that doesn’t. The one in the relational engine is useless, and then you’ve got one that’s resident in SSAS and you’ve got one that’s resident and managed in the Power BI service itself.”
“You have a good chance that you’ll go right up to the edge, and then you’ll add row-level security and go over that threshold of usability, so you have to be careful.”
“It’s a narrow but useful tool, ideal for large organizations.”
Listen to Learn
00:38 Intro to the team & topic
01:36 Episode 200 is approaching – would you like some podcast SWAG?
02:21 Compañero Shout-Outs
03:30 Row-level Security in Power BI is different from row-level security in SQL Server
06:47 The benefits of row-level security in Power BI
07:41 How you want to be implementing this for users
09:17 It might slow things down, so be careful
13:31 When do you just want to create two different reports?
15:42 You can’t limit the columns that are displayed
16:27 Will the separate row-level security pieces ever be integrated together?
17:36 This is more useful for large organizations
19:09 Closing Thoughts
Power BI Row-Level Security is completely different [than row-level security in SQL Server], uses the same exact name and is a source of confusion and frustration with customers.
Meet the Hosts
With more than 10 years of working with SQL Server, Carlos helps businesses ensure their SQL Server environments meet their users’ expectations. He can provide insights on performance, migrations, and disaster recovery. He is also active in the SQL Server community and regularly speaks at user group meetings and conferences. He helps support the free database monitoring tool found at databasehealth.com and provides training through SQL Trail events.
Eugene works as an independent BI consultant and Pluralsight author, specializing in Power BI and the Azure Data Platform. He has been working with data for over 8 years and speaks regularly at user groups and conferences. He also helps run the GroupBy online conference.
Kevin is a Microsoft Data Platform MVP and proprietor of Catallaxy Services, LLC, where he specializes in T-SQL development, machine learning, and pulling rabbits out of hats on demand. He is the lead contributor to Curated SQL, president of the Triangle Area SQL Server Users Group, and author of the books PolyBase Revealed (Apress, 2020) and Finding Ghosts in Your Data: Anomaly Detection Techniques with Examples in Python (Apress, 2022). A resident of Durham, North Carolina, he can be found cycling the trails along the triangle whenever the weather's nice enough.