Databricks / Architecture / Governance / Enterprise AI
Azure Databricks Architecture Podcast
Architecture decisions in Azure Databricks: Lakehouse versus Warehouse, designing Unity Catalog, when to use Spark, SQL or streaming, and how to build for security, governance, performance and cost.
2 episodesavg. 9 minLast update: 14 August 2026EnglishPodcast hosts Laura Bennett and Mark Sullivan
Now playing
Episode 1.1 - Designing the Enterprise Lakehouse on Azure Databricks
0:000:00
Sign in to track your progress automatically in My Learning Journey.
All episodes
Also on SpotifyLearn more?
Go deeper on the same topic.
How-tos
How to set up Unity CatalogFrom metastore to three-level namespace: the Unity Catalog setup decisions you do not get to undo later.How to set up CI/CD for Azure DatabricksTerraform for the platform, Asset Bundles for the workload: where that line sits, what belongs on each side and why you do not move it later.How to connect Azure Databricks to Microsoft PurviewRegistering and scanning Unity Catalog from Purview, including the permissions on the system tables and the difference between the two connectors.
Use cases
Manufacturing: Databricks and Fabric side by side with one governance layerA manufacturer keeps data engineering and ML on Azure Databricks and reporting in Microsoft Fabric, and connects both through Unity Catalog and Microsoft Purview into one view of lineage and access.Retail: trusted analytics with Data Products in the Unified CatalogA retail chain builds trusted, owner-backed Data Products in the Purview Unified Catalog, so analysts reuse sales, inventory and customer data without second-guessing it.Government: one Databricks workspace per domain, deployed with TerraformA large Dutch government organization gives every domain its own Azure Databricks workspace, deployed with Terraform and Databricks Asset Bundles, with Unity Catalog as the shared governance layer and a central platform team underneath.
Do you have a similar challenge?
Use the podcasts as inspiration, or share your own Data & AI challenge with us.