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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
Cost allocation, cloud tags, and other relevant things on Databricks
In this three-part video series, Databricks MVP Josue Bogran and Greg Kroleski from Databricks’ “Money Team” discuss cost allocation, tagging best practices, cloud innovations, and performance enhancements. The series explores Databricks' efforts to optimize cost reporting, leverage AI for insights, and empower businesses to make smarter, growth-driven decisions in 2024 and beyond.