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Data type is "unsupported type" of Date and Time after metadata ingestion from Databricks to Purview

Anuj Pratap Solanki 0 Reputation points
2026-04-21T06:58:20.0733333+00:00

Databricks tables are successfully ingested into Microsoft Purview Unified Catalog via Unity Catalog, and all columns are visible in the asset schema. However, columns with DATE and TIMESTAMP data types are classified as “Unsupported” in the Data Quality view. As a result, data profiling and data quality rules cannot be applied to these time-based columns.

Additionally, incremental data quality scans cannot be configured or executed because incremental scans require a supported DATE or TIMESTAMP column for time-based filtering. Since these datetime columns are marked as unsupported, they are not selectable for incremental scan configuration.

This behavior appears to be a limitation of the Microsoft Purview Data Quality engine when working with Databricks Unity Catalog datetime data types, rather than an issue related to metadata ingestion, schema visibility, permissions, or scan configuration.How to Fix this issue ?

Microsoft Security | Microsoft Purview
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  1. Smaran Thoomu 35,375 Reputation points Microsoft External Staff Moderator
    2026-04-21T07:51:51.2566667+00:00

    Hey Anuj, it looks like you’ve hit a current gap in the Purview Data Quality engine: although Unity Catalog lets you see DATE and TIMESTAMP columns in the asset schema, the Data Quality profiler today only supports a limited set of data types and marks those time-based types as “Unsupported.” That prevents both profiling/rule definition and using them as watermarks for incremental scans.

    Here’s how you can work around it today:

    1. Create a Unity Catalog view (or table) that converts your DATE/TIMESTAMP columns into a supported type • For example, in Databricks SQL:
      
           CREATE OR REPLACE VIEW catalog.my_schema.my_table_for_purview AS
      
           SELECT
      
             colA,
      
             CAST(my_date_col AS STRING)    AS my_date_col_str,
      
             CAST(my_timestamp_col AS BIGINT) AS my_ts_epoch   -- or AS STRING
      
           FROM catalog.my_schema.my_original_table;
      
      
      • By casting to STRING or a numeric type, Purview DQ will recognize the columns as “supported.”
    2. Point your Purview scan at the new view (or register it as a separate asset) • Run a full metadata & data quality scan against that view. • You’ll now see my_date_col_str or my_ts_epoch available for profiling and rule-based checks.
    3. Configure incremental scans using the new “watermark” column • In your scan settings, select my_ts_epoch (or the string representation) as the watermark for incremental filters.
    4. Keep an eye on the Purview roadmap • Full native support for Unity Catalog DATE/TIMESTAMP in Data Quality is on the backlog. You can upvote or file a feature request via Azure feedback to accelerate it.

    Hope that helps unblock you in the meantime!

    Reference docs

    • Supported data sources & file types in Purview scans

    https://docs.microsoft.com/azure/purview/purview-connector-overview

    • Configure file-type limitations & complex types

    https://docs.microsoft.com/azure/purview/sources-and-scans#file-types-supported-for-scanning

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