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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.
Databricks Workflow Backfill
Use Databricks Workflow backfill jobs to reprocess historical data, recover from outages, and handle late-arriving data efficiently.