Are you using Git in the project? It was integrated with Databricks. Are there any other tools you use?

Git is the de‑facto standard for source control. In a Databricks environment we typically store notebooks and code in a Git repository (GitHub, GitLab, Azure DevOps, etc.) and link the repo to a Databricks workspace. This allows us to pull the latest code, run notebooks from the repo, and push changes back. We also use Git for branching strategies (feature, develop, release, hotfix) and pull‑request reviews. Other tools we might use include GitHub Actions or Azure Pipelines for CI/CD, and Databricks Repos for a tighter integration. For large data projects we sometimes keep a separate data‑engineering repo for Spark jobs and a separate repo for ML models, each linked to its own Databricks workspace or cluster. The key is to keep code versioned, reviewable, and reproducible across environments.