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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
Global Job Parameters, Thanks To DABs Mutators
Declarative Automation Bundles mutators let you define job parameters once in a central config file and inject them into every job automatically at deploy time — no more copy-pasting catalog names, schema paths, and environment variables across your bundle. This post walks through a working implementation with full code examples.
Enforcing Enterprise Naming Conventions in Databricks: The Agentic Way
Naming conventions only work if they're enforced — and a Confluence page nobody reads isn't enforcement. This post walks through using Databricks Workspace Skills to make naming rules executable in Genie Code, then scaling that to a catalog-wide audit agent built with Databricks Apps and DABS. The result is automated, repeatable governance that runs without requiring engineers to opt in.
How to Pass Terraform Outputs to Databricks’ DABS
As teams migrate infrastructure definitions into Declarative Automation Bundles, Terraform still owns the Azure layer — Key Vaults, resource groups, networking. This post walks through a clean, CI/CD-ready pattern for passing Terraform outputs directly into bundle variable overrides, eliminating manual config steps and the environment drift that follows them.