Databricks Certified Data Engineer - Associate

Explanation

Databricks Repos facilitates CI/CD workflows in several key ways:

Correct Options:

1. A. Databricks Repos can facilitate the pull request, review, and approval process before merging branches - This is correct because Databricks Repos integrates with Git providers (GitHub, GitLab, Bitbucket) to enable code review workflows directly within the Databricks workspace.
2. E. Databricks Repos can commit or push code changes to trigger a CI/CD process - This is correct because when developers commit or push code changes from Databricks Repos to their Git repository, this can trigger automated CI/CD pipelines that run tests, build artifacts, and deploy changes.

Incorrect Options:

• B. Databricks Repos can merge changes from a secondary Git branch into a main Git branch - This is incorrect because Databricks Repos itself doesn't perform Git merges; Git merges are performed through the Git provider (GitHub, GitLab, etc.) or Git command line tools.
• C. Databricks Repos can be used to design, develop, and trigger Git automation pipelines - This is incorrect because while Databricks Repos integrates with CI/CD pipelines, it doesn't design or develop the automation pipelines themselves; those are typically configured in CI/CD tools like GitHub Actions, GitLab CI/CD, Jenkins, etc.
• D. Databricks Repos can store the single-source-of-truth Git repository - This is incorrect because Databricks Repos syncs with external Git repositories (GitHub, GitLab, Bitbucket) which serve as the single source of truth, not Databricks Repos itself.

Key CI/CD Workflow with Databricks Repos:

1. Developers work on code in Databricks Repos
2. Changes are committed/pushed to trigger CI/CD pipelines
3. Pull requests are created and reviewed in Databricks
4. After approval, changes are merged via the Git provider
5. CI/CD pipelines deploy the changes to production environments