How long does your business wait for a new report? A week? A month? Sometimes longer? The problem is often not Databricks, Spark, or compute. It's that every new dataset, metric, and Gold table has to go through the same Data Team. As the company grows, that team becomes the bottleneck.
This is exactly the problem Data Mesh is trying to solve. But there is surprisingly little practical guidance on what Data Mesh should actually look like in Databricks.
So I put together the guide I wish I had before implementing it:
- who should own what
- Catalogs, Schemas and Groups
- Data Products
- self-service without chaos
- governance and CI/CD
- monitoring and cost control
- how to start with one domain and scale
Not another explanation of what Data Mesh is.
A practical implementation guide for Databricks - Databricks Data Mesh Best Practices: A Practical Implementation Guide
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