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Azure Databricks Unity Catalog connector - Metadata
For the Azure Databricks Unity Catalog connector, I believe Microsoft Purview scans and collects the following technical metadata: Table name View name Column names Catalog name Schema name Metastore information Table and column descriptions from Databricks comments Unity Catalog tags, which are stored within Purview properties Table, view and column lineage where supported Storage location information may also appear within the technical properties of the asset, depending on the Databricks object. However, Microsoft does not appear to clearly document storage location as guaranteed metadata from every scan. Can anybody explain this further or confirm whether they have seen different behaviour? Where the metadata is stored or managed in Azure Databricks Metadata collected by Microsoft Purview Where it is stored or managed in Azure Databricks Metastore Unity Catalog Metastore Catalog name Unity Catalog Schema name Unity Catalog Schema Table name Unity Catalog Table metadata View name Unity Catalog View metadata Column names Table schema in Unity Catalog Table description Unity Catalog Table Comment Column description Unity Catalog Column Comment Unity Catalog tags Tags applied to Unity Catalog objects such as tables, views and columns Table and column lineage Unity Catalog lineage metadata and system lineage tables Storage location Table metadata where applicable, particularly for external tables I believe table and column descriptions are stored in Databricks as comments against the Unity Catalog object. These comments can then be scanned into Microsoft Purview and displayed as descriptions. The Microsoft documentation appears clearer for column comments than it does for table comments, so I am planning to test this myself. Does anybody have practical experience of this behaviour? Unity Catalog tags Tags are stored as metadata against Unity Catalog securable objects. Tag information can also be queried through Unity Catalog INFORMATION_SCHEMA, including TABLE_TAGS and the corresponding column tag metadata. The core Unity Catalog structure is: Unity Catalog Metastore Catalog Schema Table or View Columns Additional metadata can include: Comments Tags Lineage Storage location where applicable What Microsoft currently documents as collected by the Microsoft Purview Azure Databricks Unity Catalog connector Databricks Unity Catalog metadata Collected into Purview? Notes Metastore Yes Represented in the Purview hierarchy Catalog name Yes Unity Catalog catalog Schema name Yes Unity Catalog schema Table name Yes Creates/discovers the table data asset View name Yes Views are supported Column names Yes Schema/column metadata is collected Table comment / description Yes Your observation is correct: Databricks table comments/descriptions can appear as the Purview Data Asset description Column comments / descriptions Yes Microsoft explicitly states that Databricks column comments are displayed as column descriptions in Purview Unity Catalog tags Yes Microsoft explicitly states that Unity Catalog tags are scanned into Purview Properties Table/view lineage Yes, subject to prerequisites Extracted from Unity Catalog system lineage tables Column lineage Yes, subject to prerequisites Supported, although there are lineage limitations External tables Metadata yes External table metadata is supported; lineage for external tables is not supported Microsoft's connector documentation currently lists the following core hierarchy and metadata as being extracted by the scan: Metastore Catalogs Schemas Tables and Columns Views and Columns Unity Catalog Tags Data Asset descriptions This behaviour appears to be genuine. Microsoft specifically documents that a Databricks column comment can be used as the description displayed in Microsoft Purview. Microsoft also notes that setting a Databricks table column comment to an empty string prevents the column description from being displayed in Purview. For practical purposes, the relationship is: Databricks comment or description Purview scan Microsoft Purview description This is explicitly documented for column comments. Table comments also appear to be surfaced as the Data Asset description through the connector, based on observed behaviour, although Microsoft's documentation is less explicit about this. Has anybody seen this working consistently for table descriptions? Unity Catalog tags Unity Catalog tags are supported by the current connector. Microsoft documentation states that tags from Unity Catalog are extracted during scanning and displayed within Microsoft Purview Properties. There is a documented exception where tags are not supported when the scan uses the Kubernetes Self-hosted Integration Runtime option. That exception should not apply where Kubernetes SHIR is not being used. Storage location The official connector documentation clearly documents the Unity Catalog hierarchy and the metadata listed above. However, it does not appear to explicitly list the table storage location or storage path as a guaranteed metadata element within the supported metadata capabilities. Storage location information may therefore appear for some Databricks objects, particularly external tables, but I would not currently treat it as guaranteed metadata from every Purview Unity Catalog scan without further testing. My current understanding is that a Microsoft Purview scan of Azure Databricks Unity Catalog can collect: Metastore Catalog Schema Table View Columns Table descriptions or comments Column descriptions or comments Unity Catalog tags Table and view lineage where supported Column lineage where supported External table metadata Storage location may also be visible where applicable, but this appears less clearly documented as a guaranteed field? Does this sound correct based on other people's experience of Microsoft Purview scans of Azure Databricks Unity Catalog data sources?
Acessos pastas SharePoint / SharePoint folder access
É possível identificar somente acessos a pastas do SharePoint? Algumas informações internas da companhia foram vazadas e precisamos saber quem acessou a pastas do Sharepoint onde estavam essas informações. Outra situação, é que conseguimos identificar que nessa mesma pasta alguns arquivos foram baixados, mas no relatório o usuário aparece "app@sharepoint". Alguém saberia explicar? It is possible to identify access to SharePoint folders? Some of the company's international information was leaked, and we need to know who accessed the SharePoint folders containing that data. Another issue is that we identified files being downloaded from that same folder, but the user appears as "app@sharepoint". Could anyone explain this?
Purview archive shipped. Delete policy is still armed.
Roadmap 561208 went GA over the last few weeks with very little noise. Purview retention policies in Data Lifecycle Management can now move inactive OneDrive and SharePoint content into Microsoft 365 Archive. The framing is storage cost. I want to talk about something else, because I think there's a gap here that's going to catch people out, and I'd like to know whether anyone else is seeing it. Archive is a storage tier. It is not a retention state. An archived SharePoint site stays fully in scope of every retention policy that applied to it while it was active. Nothing about archiving protects content. Now layer that onto conflict resolution. Retention beats deletion, so a site policy set to delete after 2 years goes dormant while a label is retaining the item. Dormant, not cancelled. So picture this: A file carries a retention label with a 4-year retention period. The site it lives on has a delete-after-2-years retention policy. The label's end-of-retention action is deactivate retention settings. For four years, everything looks correct. The label holds. The delete policy sits there doing nothing. Then the label reaches end of retention and deactivates. The shield is gone. The delete instruction wakes up, unopposed, two years overdue, and the file goes. Not to archive. Just gone. The reflex here is "explicit wins over implicit." It doesn't apply. That principle only arbitrates between competing delete actions. A label that expires with no delete action of its own brings nothing to the contest. There is no explicit action to outrank the policy with. "Do nothing" sounds like a safe default. It's actually a decision to stop defending the file. Right now you cannot set a label to archive at end of retention. The options are deactivate, delete automatically, disposition review, or hand it to a Power Automate flow. Archive isn't on the list. Microsoft shipped archive at the policy level and left the label level to flows and webhooks. That reads to me like they know the gap exists and haven't decided how to close it. And here's my suspicion about why this shipped now. Archived content is excluded from Copilot indexing. That's Microsoft's own framing in the message center post. Which suggests this feature is going to evolve on Copilot's roadmap rather than records management's. The moment "archive" becomes the button you press to clean up Copilot's answers, people will press it constantly, at scale, without once checking what policy is sitting underneath. Meanwhile Exchange has nothing. Purview retention still can't move mail into an archive mailbox, and we're all still running MRM tags next to Purview years after being told MRM was legacy. Has anyone hit the deactivate-into-delete scenario in a live tenant, or is this still theoretical? And does anyone read the label-level gap differently than I do? Genuinely open to being told I've got this wrong.Published Glossary Terms Not Appearing When Editing Microsoft Purview Data Assets
Help and Support for All Problem Published glossary terms were not available for selection when editing Data Map assets in Microsoft Purview. Although the glossary terms had been created and published within Governance Domains, and the user had the appropriate permissions, the Glossary Terms dropdown remained empty. This prevented glossary terms from being assigned to data assets or individual columns. Symptoms The following behaviour was observed: Published glossary terms existed within Governance Domains in the Unified Catalog. User permissions had been verified and were correctly configured. The Glossary Terms field was visible when editing a Data Map asset. The dropdown opened successfully but did not display any available glossary terms. Glossary terms could not be associated with data assets or columns. Root Cause The issue occurred because Asset Curation had not been enabled in Microsoft Purview. Although glossary terms had been created and published within Governance Domains in the Unified Catalog, the Data Map asset curation experience had not been configured to use Unified Catalog glossary terms. As a result, the Glossary Terms field was displayed when editing an asset, but no terms were available for selection. Microsoft Purview requires Asset Curation to be enabled and configured before Unified Catalog glossary terms can be assigned to Data Map assets and columns. Resolution The following steps resolved the issue: Confirmed that no Classic Glossaries, Classic Glossary Terms or Term Templates existed in the Purview account. Enabled Asset Curation (Preview). Configured Microsoft Purview to use Unified Catalog Glossary Terms. Completed the Asset Curation configuration wizard. Edited a Data Map asset and verified that published glossary terms were now displayed. Successfully assigned glossary terms to both Data Map assets and individual columns. Because no Classic Glossary content existed, there was no glossary content that required migration. Outcome After Asset Curation was enabled and configured, published Unified Catalog glossary terms became available in the Glossary Terms dropdown when editing Data Map assets. Glossary terms could then be successfully assigned to both assets and columns. Key Takeaway Creating and publishing glossary terms within Governance Domains is not sufficient on its own. To use Unified Catalog glossary terms when curating Data Map assets and columns, Asset Curation must also be enabled and configured to use Unified Catalog Glossary Terms.
Missing activity names from Audit Log documentation
We all know that the documentation team is A-tier and amazing at what they do and isn't just copy and pasting marketing materials. But I've noticed that some really obscure functionalities like 'user registered a device' or 'user joined a device' or about half the other things a user can do, are not documented on this list of activity names. The ironically named 'friendly' list doesn't work. So I actually can't audit the unfamiliar devices under our tenants? It appears that this KB is actually locked down, so more can't be added when they are discovered. How are we supposed to use the tool Microsoft has forced everyone towards, when the Documentation team is too bad to document anything, so they outsource it to the community (Microsoft victims), but then they lock down contributions (presumably, because they have some metric that keeps them from being useful - atleast based on my interactions with them). Documentation seems to be a massive fail on Microsoft's part. How did it get this way? Is there a reliable way of finding the activity name - one that ISN'T some preview Graph endpoint that I can't teach my techs to use, because I'm not teaching my techs to program?
Struggling with running DQ Scans (Long queuing and Retry Count Error Issues)
Hi everyone, I have been exploring Microsoft Purview Data Quality quite extensively. At this point, I have configured more than 4,000 data quality rules across more than 10 Microsoft Fabric capacities, each with a minimum capacity of F16. Fabric is the source for all assets registered in Purview. I have identified several issues with the product, but the two that are currently impacting me the most are the following: DQ scans failing with a generic error“Max Retry Count Reached. Ending Workflow. Current Task HandleError”The challenge is that the error message does not identify which rule is causing the failure. As a result, I have to troubleshoot manually by disabling groups of rules, rerunning the scans, and repeating the process until I find the problematic rule. This trial-and-error approach is very time-consuming, especially at this scale. This seems to be caused by issues in some of the DQ rules, even though all rules are marked as “Good to go” in Purview. When running Data Quality scans, I often receive the following error: DQ scans remain queued for a long timeI am not sure why this happens or what resource, orchestration, or scheduling constraint is causing the delay. Whenever I run these DQ scans, they remain in a Queued state for at least 10 minutes, even when there is nothing running on the Fabric capacities. Has anyone experienced similar behavior with Purview Data Quality at this scale? Specifically, I would appreciate any guidance on: How to identify which DQ rule is causing a scan failure Why scans remain queued even when Fabric capacity appears to be idle Whether there are known limitations or best practices for running thousands of DQ rules in Purview Thank you.Glossary Terms Governance Model
A practical implementation pattern that scales from a Proof of Concept to enterprise deployment. If you're involved in implementing Microsoft Purview or designing an enterprise data governance model, I'd be interested to hear how you're approaching glossary management within your organisation. Do you manage a single enterprise glossary, separate domain glossaries, or a combination of both? I'd love to hear your experiences and any lessons you've learned. https://www.linkedin.com/search/results/all/?keywords=%23microsoftpurview&origin=HASH_TAG_FROM_FEED https://www.linkedin.com/search/results/all/?keywords=%23microsoft&origin=HASH_TAG_FROM_FEED https://www.linkedin.com/search/results/all/?keywords=%23datagovernance&origin=HASH_TAG_FROM_FEED https://www.linkedin.com/search/results/all/?keywords=%23unifiedcatalog&origin=HASH_TAG_FROM_FEED https://www.linkedin.com/search/results/all/?keywords=%23enterprisedatacatalogue&origin=HASH_TAG_FROM_FEED https://www.linkedin.com/search/results/all/?keywords=%23metadata&origin=HASH_TAG_FROM_FEED https://www.linkedin.com/search/results/all/?keywords=%23metadatamanagement&origin=HASH_TAG_FROM_FEED https://www.linkedin.com/search/results/all/?keywords=%23dataproducts&origin=HASH_TAG_FROM_FEED https://www.linkedin.com/search/results/all/?keywords=%23datamesh&origin=HASH_TAG_FROM_FEED https://www.linkedin.com/search/results/all/?keywords=%23federatedgovernance&origin=HASH_TAG_FROM_FEED https://www.linkedin.com/search/results/all/?keywords=%23enterprisearchitecture&origin=HASH_TAG_FROM_FEED https://www.linkedin.com/search/results/all/?keywords=%23dataarchitecture&origin=HASH_TAG_FROM_FEED https://www.linkedin.com/search/results/all/?keywords=%23informationarchitecture&origin=HASH_TAG_FROM_FEED https://www.linkedin.com/search/results/all/?keywords=%23datamanagement&origin=HASH_TAG_FROM_FEED https://www.linkedin.com/search/results/all/?keywords=%23azure&origin=HASH_TAG_FROM_FEED https://www.linkedin.com/search/results/all/?keywords=%23microsoft365&origin=HASH_TAG_FROM_FEED https://www.linkedin.com/search/results/all/?keywords=%23purview&origin=HASH_TAG_FROM_FEED https://www.linkedin.com/search/results/all/?keywords=%23glossary&origin=HASH_TAG_FROM_FEED https://www.linkedin.com/search/results/all/?keywords=%23businessglossary&origin=HASH_TAG_FROM_FEED https://www.linkedin.com/search/results/all/?keywords=%23dataskylabstudio&origin=HASH_TAG_FROM_FEED 😀 Understanding the Enterprise and Local Glossary Terms Governance Model This diagram demonstrates a scalable approach to managing Glossary Terms in Microsoft Purview Unified Catalog. The objective is simple: Create enterprise business terminology once, reuse it across the organisation, and keep specialist business terminology within the Governance Domain that owns it. This approach creates a Single Source of Truth for shared business language, reduces duplication, improves consistency and allows the governance model to scale as the organisation grows. Step 1 – Create an Enterprise Glossary Terms Governance Domain The first step is to create a dedicated Governance Domain specifically for Enterprise Glossary Terms. For example: Enterprise Glossary Terms This Governance Domain becomes the central location where enterprise-wide business terminology is created, maintained and governed. Examples include: Party Person Organisation Customer Employee Product Account Contract Invoice Order Transaction These are business concepts that are commonly used across multiple business functions and Governance Domains. Each Enterprise Glossary Term has: One agreed business definition. One accountable owner. One authoritative source. One location where it is maintained. Unlimited reuse across Data Products. Think of this Governance Domain as the organisation's enterprise business dictionary. Step 2 – Create Business Governance Domains Next, create Governance Domains that reflect your organisational structure. For example: Finance Sales Human Resources Meat, Dairy & Approved Establishments Each Governance Domain is responsible for: Its own Data Products. Its own local Glossary Terms. Its own stewardship and governance. Step 3 – Create Local Glossary Terms Not every business term belongs in the Enterprise Glossary. Many terms are only relevant to a single business function and should remain owned within that local Governance Domain. For example: Finance General Ledger Cost Centre Budget Code Payment Run Sales Sales Channel Campaign Opportunity Discount Code Human Resources Job Grade Leave Type Shift Pattern Pay Band Meat, Dairy & Approved Establishments Establishment Type Hygiene Rating Carcass Classification Milk Cooler Capacity These Local Glossary Terms remain within their own local Governance Domain because they are not intended for enterprise-wide reuse. They can be seen in the Enterprise Glossary. Step 4 – Create Data Products Each Governance Domain creates the Data Products it owns. Examples include: Finance Financial Reporting Sales Sales Orders Human Resources Employee Directory Meat, Dairy & Approved Establishments Establishment Inspections The Data Product becomes the business representation of a collection of related data. Step 5 – Reuse Enterprise Glossary Terms When creating a Data Product, associate the Enterprise Glossary Terms that describe the business concepts used by that Data Product. For example: Financial Reporting Uses: Customer Account Transaction Invoice Sales Orders Uses: Customer Product Contract Order Employee Directory Uses: Person Employee Organisation Establishment Inspections Uses: Organisation Party Product Notice that these Enterprise Glossary Terms are not recreated inside each Governance Domain. Instead, they are referenced from the Enterprise Glossary Terms Governance Domain. This is the key principle behind the model: Create once. Reuse many times. Step 6 – Add Local Glossary Terms Each Data Product can also reference Local Glossary Terms from its own Governance Domain. For example: Financial Reporting Also uses: General Ledger Cost Centre Sales Orders Also uses: Sales Channel Employee Directory Also uses: Job Grade Establishment Inspections Also uses: Inspection Risk Category Each Data Product therefore combines: Enterprise Glossary Terms Local Glossary Terms This provides consistent enterprise language while still allowing each business area to manage its own specialist terminology. Why this model works This implementation separates enterprise business language from specialist business language. Enterprise Glossary Terms provide: A Single Source of Truth. One agreed definition. One accountable owner. Reuse across every Governance Domain. Local Glossary Terms provide: Business-specific terminology. Local ownership. Specialist business knowledge. Flexibility without affecting enterprise standards. Together they provide: Reduced duplication. Consistent business language. Easier governance. Better Discovery Search. Simpler maintenance. Reusable metadata. A scalable governance model. Relationship with the Conceptual Data Model The Enterprise Glossary answers the question: What business concepts does the organisation use? The Conceptual Data Model answers: How are those business concepts related? For example: Customer │ places│ ▼ Order │ contains ▼ Product The Enterprise Glossary defines each business concept. The Conceptual Data Model describes how those concepts relate to one another. Together they establish a common business language that can be reused consistently across Governance Domains, Data Products and the wider Enterprise Data Catalogue. Microsoft Purview Implementation Steps Create a Governance Domain called Enterprise Glossary Terms. Create enterprise-wide Glossary Terms within this Governance Domain. Assign an accountable owner for each Enterprise Glossary Term. Create business Governance Domains that reflect the organisation. Create Local Glossary Terms only where the terminology is unique to that Governance Domain. Create Data Products within each Governance Domain. Associate Enterprise Glossary Terms with Data Products wherever the same business meaning applies. Associate Local Glossary Terms with Data Products where specialist business terminology is required. Continue expanding the Enterprise Glossary as new shared business concepts emerge. Key Principle Create once. Reuse everywhere. Keep local terms local. Enterprise Glossary Terms establish the organisation's shared business language, while Local Glossary Terms allow individual Governance Domains to manage specialist terminology. Together they provide a scalable governance model for Microsoft Purview Unified Catalog that supports Federated Data Governance, Data Mesh principles, and long-term enterprise growth without unnecessary duplication of business definitions.Microsoft Purview Unified Catalog; Governance Domains and Business Concepts
I've been using the attached artefacts for some time to help explain the knowledge exchange aspects of Microsoft Purview Unified Catalog, particularly how Governance Domains and Business Concepts work together to provide business context, ownership, stewardship and operational insights. They have been useful in workshops with data architects, governance professionals, product owners and business stakeholders to demonstrate how concepts fit together within a governance domain and contribute towards trusted information and better business outcomes. I'm interested in hearing from the wider Purview community: Do these artefacts accurately represent the intent and capabilities of Governance Domains within Microsoft Purview? Are there any concepts that you feel are missing, over-emphasised, or could be represented more clearly? How are others explaining Governance Domains and Business Concepts to non-technical stakeholders? Any feedback, suggestions, or alternative approaches would be greatly appreciated. I'm always looking to refine these materials and make them more useful for organisations adopting Purview Unified Catalog. #MicrosoftPurview #DataGovernance #DataManagement #Metadata #DataProducts #MicrosoftData #Purview #DataArchitecture #UnifiedCatalog
