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AndySteinke
Frequent Visitor

Dynamic Data Masking in Warehouse / Lakehouse?

We are implementing dynamic data masking (using data from purview) in our Synapse dedicated SQL pools and want to know if we are going to be able to do the same kind of thing in Fabric Warehouses and Lakehouses.  Is this possible yet and if so, how?  Thanks!

 

 

1 ACCEPTED SOLUTION
GeethaT-MSFT
Community Support
Community Support

Hi @AndySteinke Thanks for posting your question in Microsoft Fabric Community

It is going to be a three-step solution

1. First, we will enable dynamic data masking for SQL Endpoints (Lakehouse) and Warehouse. This will come by GA (timelines are all not guaranteed) - with this solution, you can set masking rules in each lakehouse and warehouse individually and you will be honored only when you query via the respective endpoints.
2. As a next step, we will enable dynamic data masking at OneLake - called OneSecurity. The benefit is, you set the masking rules in Lakehouse, and all other engines that is consuming that Lakehouse (Spark, Kusto, PowerBI, etc.) will all honor that masking rule. This will come later (no ETA yet) - still, masking rules are set at individual artifacts (lakehouse, warehouse, etc)
3. As a third step - we will provide masking policy definitions via a central management plane (Purview) - whereby you can set masking policy based on a detected classification label and apply it across the organization - to multiple lakehouses and warehouses. For example, you go to a studio, you will search for an attribute (SSN, credit card), you will define a masking rule based on the sensitivity of that attribute, and we will apply it across wherever we find that attribute. This will come later as well (no ETA).

 

I hope this information helps

 

------------------------------------------------------------------------------------------------------------------------------ 

   If this answers your question, please consider accepting the solution by hitting the **Accept as Solution** 👍as it helps the community look for answers to similar questions. 
-------------------------------------------------------------------------------------------------------------------------------

Regards

Geetha

 

View solution in original post

1 REPLY 1
GeethaT-MSFT
Community Support
Community Support

Hi @AndySteinke Thanks for posting your question in Microsoft Fabric Community

It is going to be a three-step solution

1. First, we will enable dynamic data masking for SQL Endpoints (Lakehouse) and Warehouse. This will come by GA (timelines are all not guaranteed) - with this solution, you can set masking rules in each lakehouse and warehouse individually and you will be honored only when you query via the respective endpoints.
2. As a next step, we will enable dynamic data masking at OneLake - called OneSecurity. The benefit is, you set the masking rules in Lakehouse, and all other engines that is consuming that Lakehouse (Spark, Kusto, PowerBI, etc.) will all honor that masking rule. This will come later (no ETA yet) - still, masking rules are set at individual artifacts (lakehouse, warehouse, etc)
3. As a third step - we will provide masking policy definitions via a central management plane (Purview) - whereby you can set masking policy based on a detected classification label and apply it across the organization - to multiple lakehouses and warehouses. For example, you go to a studio, you will search for an attribute (SSN, credit card), you will define a masking rule based on the sensitivity of that attribute, and we will apply it across wherever we find that attribute. This will come later as well (no ETA).

 

I hope this information helps

 

------------------------------------------------------------------------------------------------------------------------------ 

   If this answers your question, please consider accepting the solution by hitting the **Accept as Solution** 👍as it helps the community look for answers to similar questions. 
-------------------------------------------------------------------------------------------------------------------------------

Regards

Geetha

 

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