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Most teams that move to Databricks get the hard part right. They migrate the processing engine, rebuild the transformation logic, and stand up Unity Catalog. Then they leave Azure Data Factory running in the background: connected to everything, owned by nobody, and quietly accumulating cost and complexity. In this entry, that’s the gap we address.
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ML & AI
Why Your Databricks Upgrade Is Incomplete If You're Still Running ADF
Still running ADF after moving to Databricks? Here's why it happens, what it's costing your governance story, and how Lakeflow Jobs closes the gap.
CI/CD Best Practices: Passing tests isn't enough
CI/CD pipelines can pass all jobs yet still deploy broken functionality. This blog covers smoke testing, regression testing, and critical validation strategies: especially useful for data projects where data quality is as important as code quality.
Stop ELT Headaches: Why We Partner with Fivetran + Databricks
Discover how SunnyData overcame ELT challenges by partnering with Fivetran and Databricks, creating reliable data pipelines that eliminate late-night fixes and accelerate insights.