Learn how to safely version, test, and deploy Databricks AI/BI dashboards using Git and CI/CD to deliver reliable analytics at scale.

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Production dashboards that drive business decisions need the same deployment discipline as production code. Using Databricks Asset Bundles and Git, analytics teams can version, review, and deploy AI/BI dashboard changes through a CI/CD workflow. The process covers: adding a dashboard to a Git-backed Asset Bundle, branching for safe edits, opening pull requests for peer review, deploying with environment-specific configuration (dev/test/prod catalogs), and rolling back changes when issues arise. The workflow doesn't change how dashboards are authored day-to-day but adds traceability, reviewability, and safe rollback capabilities.

Tutorial: How to ship AI/BI Dashboard changes safely at scale with Databricks Asset Bundles

Introduction: A structured workflow for shipping dashboard changes safely

Bonus 1: What if you want to inspect the history?

Bonus 2: What if you need to revert a change?