Get certified for free when you join Fabric Data Days 2026 and dive into Fabric, Power BI, SQL, AI, and other essential data skills.
Join nowData Days is here! Join us now for 60+ days of learning, challenges, and connection. Learn more
Data loss prevention (DLP) policies help you govern the sensitive information managed in your Power BI tenant and comply with governmental or industry regulations, such as GDPR (the European Union’s General Data Protection Regulation). Earlier this year, we announced the release of DLP policies for Power BI to public preview.
We’ve seen impressive results with DLP policies in Power BI, with tenants scanning tens of thousands of datasets per day, and more. DLP policies provide you with an automatic solution to govern sensitive business data in your Power BI tenant, at scale.
We're happy to share with you two significant enhancements to DLP policies in Power BI:
With each of these actions, Power BI will evaluate the dataset to determine if it contains sensitive information or not. This process utilizes CPU from the premium capacity associated with the workspace the evaluated dataset resides in. The CPU consumption of the evaluation will be equal to 30% of the CPU consumed by the refresh action that triggered the evaluation. For example, if a refresh action costs 30 milliseconds of CPU, then the DLP scan will cost an additional 9 milliseconds. The fixed 30% additional CPU consumption for the DLP evaluation can help you predict the impact of DLP policies on your overall Capacity CPU utilization, and perform capacity planning when rolling out DLP policies in your organization.
*To clarify, there is no additional CPU metering due to DLP evaluation for Premium Per User workspaces, as they are not associated to Premium capacities.
To see the CPU usage of your data loss prevention policies, go to the “Power BI Premium Capacity Metrics App”. For more information visit Monitor Power BI Premium capacities with the Premium Capacity Metrics app. - Power BI | Microsoft Do...
In the dataset’s detail page, you will now be able to see all the policy rules that have been matched for this dataset. By clicking on the "view all" in the top yellow banner, you will open a side panel with a card representing each and every rule. On top of viewing all the matched rules, data owners will be able to take action if they believe the data was falsely identified.
Based on how the policy rule was configured, you will be able to see one or a combination of these actions:
You must be a registered user to add a comment. If you've already registered, sign in. Otherwise, register and sign in.