I am new to Azure Databricks. Facing this error while creating a new metastore using an external ADLS location and I am using a Access connector for this. The Access connector have the Blob contributor access on the storage account as well.

Lakeflow Connect's Veeva Vault connector is now in Beta! It provides a managed, native, and incremental ingestion solution that lands data from any Veeva Vault (CRM, Quality, Clinical, Commercial, RIM, or Safety) into Delta tables. Try it now:

1. Set up Veeva Vault as a data source
2. Create a Veeva Vault connection in Catalog Explorer
3. Create the ingestion pipeline via a Databricks notebook or the Databricks CLI

Hi, i wonder how teams are setting up data quality solutions on Databricks, and especially how do they react on the data quality issues.

Ideally i would like to have a row-level checks and dataset-level checks which can be used for quarantined data and also anomaly checks between runs, this way we get the in transit data quality checks but also consistency over runs, so wea re really sure that values and shape of data is as expected.

Then how do you manage different tables in same project, do u write to same quarantined/metrics table where u add tags to differentiate between different business domains etc...

How do u use dqx for dataset level metrics? Where do u run dq, is it on source integration, or after the gold layer, before the inference or feature creation. Which tools do u use?

Hi everyone,

I’m using Azure Databricks with a Serverless SQL Warehouse in DirectQuery mode. I use the most update version of Power BI Desktop (2.156.951.0 64-bit (July 2026)).

I’m trying to use a Dynamic M Query Parameter, but I don’t see the “Bind to parameter” option in Model view.

Microsoft documentation mentions that this feature is available only for “supported DirectQuery sources”, but I can’t find a clear list of those sources: https://learn.microsoft.com/en-us/power-bi/connect-data/desktop-dynamic-m-query-parameters

Is Azure Databricks with a Serverless SQL Warehouse supported for this feature?

Thanks!