Classification on DataBricks
Hello everyone, I would like to request an updated confirmation regarding the correct functioning of custom classification for Databricks Unity Catalog data sources. Here is my current setup: The data source is active. Source scanning is working correctly. I created the custom classification in “Annotation management / Classifications”. I created and successfully tested the regular expression under “Annotation management / Classification Rules”. I generated the Custom Scan Rule Set in “Source management / Scan Rule Sets”, associated to Databricks and selecting the custom rule. However, when running the scan on Databricks: I do not find any option to select my Scan Rule Set (for another source like Teradata, this option is visible). No classification findings are generated based on my custom rule. Other tests do produce findings (system-generated). Does anyone have insights on what I should verify? Or is this custom classification functionality not supported for Databricks?
Purview Data Map scanning Microsoft Fabric and no classifications applied or scan rule sets
Microsoft Purview cannot currently apply built-in or custom classifications (including sensitive information types) to metadata discovered from Microsoft Fabric workspace scans. While Purview can register Fabric workspaces and extract structural metadata (workspaces, Lakehouses, Warehouses, tables, columns, and limited lineage), classification rules are not executed against Fabric assets in the same way they are for supported sources such as Azure SQL, ADLS Gen2, or on-prem databases. This results in classification gaps across a core enterprise analytics platform. Why This Is a Significant Service Omission 1. Breaks the Core Value Proposition of Purview 2. Undermines Regulatory and Risk Management Controls 3. Creates an Inconsistent Governance Experience 4. Blocks Downstream Purview Capabilities 5. Forces Anti-Patterns and Workarounds The lack of automated classification support for Microsoft Fabric workspace data represents a material service omission in Microsoft Purview, significantly limiting its effectiveness as a unified data governance platform and introducing avoidable compliance, operational, and assurance risks—particularly in regulated environments. Are there plans to improve this and if so what are the timescales?
Lineage Limitation on Wide Power BI Semantic Models & Built-in Classification Rule Sets
Hello everyone, I’m evaluating the new Microsoft Purview Governance Portal for our finance data governance needs. Previously with the Azure Purview classic version we had a couple of blocking issues such as it failed to scan wide semantic models. But now we're migrating to Fabric and we'd like to try the new Microsoft Purview Governance Portal. I’d appreciate any insights or confirmation from the product team or the community. Lineage Limitation on Wide Power BI Semantic Models Background: When we first ran the Purview Data Map Scanner against our finance semantic model, it failed once the total column count across all tables exceeded roughly 500 columns. In our case, a single SAP table alone has about 450 columns—so the scan wouldn’t complete, and we couldn’t capture any lineage. Questions: Has Purview removed or raised any “hidden” column-count limits for Power BI semantic models? Is there any official documentation on maximum supported column counts (e.g. 200, 500, or otherwise)? Are there recommended workarounds for very wide models—such as splitting into sub-datasets, using incremental scans, etc. to get full lineage? 2. Built-in Classification Rule Sets Background: Purview ships with a set of Microsoft-provided “Sensitive Information Types” that appear in every scan rule set. In many of our scans these defaults aren’t needed, and they clutter the results. Questions: Can we delete or permanently disable the built-in classification rules? If not, what’s the best way to ensure they’re not applied during a full scan? Are there any APIs or PowerShell commands that let us automate the exclusion of Microsoft’s defaults from our scan rule sets? Thank you in advance for any pointers, documentation links, or best-practice advice!