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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
Hidden Magic Commands in Databricks Notebooks
Discover 12 powerful Databricks notebook magic commands beyond %sql and %python. Learn shortcuts for file operations, performance testing, and debugging.
Snowflake and Databricks: How to balance compute
Compare Snowflake and Databricks compute models. Learn scaling strategies, cost optimization tips, and when to use auto-suspend, multi-cluster, and autoscaling.
SQL: Why Materialized Views Are Your Simplest Data Transformation Tool
Create cost-effective, incremental materialized views in Databricks SQL Warehouse. Includes monitoring tips, best practices, and Enzyme optimization.