*For this entry exists the more relevant or more recent entry MC937920
check before: 2026-06-01
Product:
Fabric, Purview, Purview Communication Compliance, Purview compliance portal, Purview Data Loss Prevention
Platform:
Web, World tenant
Status:
In development
Change type:
Links:
Details:
Your organization can now control who can access your data depending on the sensitive information detected in Fabric semantic models and lakehouses. DLP restrict access action allows you to block access to guest users or all users depending on what labels or sensitive information types matches your semantic models or lakehouses. This is in addition to the ability already supported by DLP policies to audit and notify users via Policy Tips based on sensitive content within Fabric semantic models and lakehouses.
Change Category:
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Scope:
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Release Phase:
Preview, General Availability
Created:
2024-11-19
updated:
2026-01-21
Public Preview Start Date
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Docu to Check
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MS workload name
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summary for non-techies**
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Direct effects for Operations**
Please, look at the most relevant linked item for details
explanation for non-techies**
Imagine your organization as a library. In this library, there are books that contain sensitive information, like personal details or confidential business strategies. You want to ensure that only the right people can read these books, especially if they contain sensitive content.
Microsoft Purview's new feature is like a smart librarian who checks each book before handing it out. This librarian uses special glasses (semantic models) to see if the book contains sensitive information. If it does, the librarian can decide who gets to read it. For example, if a book is labeled as containing sensitive information, the librarian might only allow trusted staff to read it and block access to guest visitors.
Previously, the librarian could only keep a record of who wanted to read these sensitive books and give them a gentle reminder about the importance of handling such information carefully. Now, with this new feature, the librarian can take a more active role by actually preventing certain people from accessing the books based on their content.
This feature is particularly useful for organizations that want to maintain strict control over who can access sensitive data. It ensures that sensitive information is only accessible to those who need it, helping to protect the organization from potential data breaches or leaks. Just like in a library, where you want to keep rare or important books safe, this feature helps keep your organization's sensitive data secure.
** AI generated content. This information must be reviewed before use.
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change history
| Date | Property | old | new |
| 2026-01-21 | RM Product Tags | Microsoft Purview compliance portal | Microsoft Purview |
| 2025-12-04 | RM Release | October CY2025 | June CY2026 |
| 2025-11-17 | RM Preview | November CY2024 | April CY2024 |
| 2025-07-02 | RM Release | December CY2025 | October CY2025 |
| 2025-03-27 | RM Release | April CY2025 | December CY2025 |
| 2025-03-27 | RM Title | Microsoft Purview compliance portal: Data Loss Prevention - Restrict access action support for semantic models in Fabric | Microsoft Purview compliance portal: Data Loss Prevention – Restrict access action support for sematic models and lakehouses in Fabric |
| 2025-03-27 | RM Description | Your organization can now control who can access your data depending on the sensitive information detected in Fabric semantic models. DLP restrict access action allows you to block access to guest users or all users depending on what labels or sensitive information types match your sematic models. This is in addition to the ability already supported by DLP policies to audit and notify users via Policy Tips based on sensitive content within Fabric semantic models and lakehouses. | Your organization can now control who can access your data depending on the sensitive information detected in Fabric semantic models and lakehouses. DLP restrict access action allows you to block access to guest users or all users depending on what labels or sensitive information types matches your semantic models or lakehouses. This is in addition to the ability already supported by DLP policies to audit and notify users via Policy Tips based on sensitive content within Fabric semantic models and lakehouses. |
Last updated 4 weeks ago ago