Data sharing with another area

Hi Anonymous , 
To cater this problem It is recommended to create a new dataset with restricted columns & grant 'Build' access
You can follow these steps :

Step 1 – Create a new Power BI dataset

  Open Power BI Desktop.

  Instead of connecting directly to the dataflow, connect to your existing published dataset:

  Home → Get Data → Power BI datasets → choose your existing model (the one with fopag).

  You’ll now have a live connection to your dataset.

  In Model view, only select or keep the fields and tables they need (exclude salary/compensation).

  Save and publish this as a new dataset (e.g., Fopag_Restricted).

  This new dataset automatically stays updated when the original refreshes.

Step 2 – Grant “Build” access

  In the Power BI Service:

  Go to the new dataset’s settings → Manage permissions.

  Add the group or users from that area.

  Give them Build permission.

  That allows them to:

  Connect directly to your dataset using Power BI Desktop or Excel.

  Create their own reports or models that stay synced with your data.

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Hi Anonymous,

Here’s how I’d enable “automatic” consumption while protecting compensation columns.

1. Use a semantic model with Object-Level Security (OLS)
   Build a dataset on top of fopag and apply OLS to hide the compensation columns from that specific area. Grant them Build permission on the dataset so they can connect to it (Live connect, Analyze in Excel, or their own reports) without ever seeing those columns. OLS lets you secure specific columns/tables in a model. See: Object-level security (OLS).
2. Or publish a curated “safe” table and share it via OneLake/Warehouse
   Have Dataflow Gen2 write fopag (minus compensation columns) to a Lakehouse/Warehouse in a shared (or new) workspace, then:
   • Share it via OneLake shortcuts to the requesting area’s workspace (no copying, central governance). See: OneLake shortcuts.
   • Or expose it through the Warehouse SQL endpoint so they can pull it directly with ODBC/JDBC/SQL tools into their BI. See: Connect to Fabric Data Warehouse and Warehouse connectivity.
   Dataflow Gen2 supports writing directly to Lakehouse/Warehouse destinations. See: Dataflow Gen2 destinations.
3. Label and govern the data
   Apply sensitivity labels (e.g., “Confidential – HR”) to the dataset/table so protection and auditing follow the data across exports and usage. See: Sensitivity labels in Power BI and Information protection in Fabric.

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But how do I select only the columns I want to keep?

After loading the data as a live connection, there seems to be an option to hide the column/table—but it is disabled for me.

Hi Anonymous 


We’d like to check if you were able to go through the previous response to your issue. Please let us know if you need further clarification we’ll do our best to support you.