Answer: From the UX Authoring canvas, select Set up code repository., Create a Git repository.

To implement version control for Azure Data Factory pipeline artifacts and ensure existing resources in the UX Authoring canvas are version-controlled, the correct approach involves two key steps: **A. From the UX Authoring canvas, select Set up code repository** - This is the primary action within Azure Data Factory to configure Git integration. When you select this option, you can connect ADF to an existing Git repository or create a new one directly through the setup process. This configuration enables tracking of all changes to pipeline artifacts in version control. **B. Create a Git repository** - A Git repository is the fundamental requirement for version control. While option A's setup process can create a repository, explicitly creating one ensures you have the version control system ready before or during the ADF configuration. The repository will store all pipeline artifacts as JSON files, maintaining their version history. **Why other options are incorrect:** - **C (Create a GitHub action)**: GitHub Actions are for CI/CD automation, not for implementing the core version control functionality itself. - **D (Create an Azure Data Factory trigger)**: Triggers are for pipeline execution scheduling, unrelated to version control implementation. - **E (From the UX Authoring canvas, select Publish)**: Publishing saves changes to the data factory service but doesn't implement Git-based version control. - **F (From the UX Authoring canvas, run Publish All)**: Similar to E, this publishes changes but doesn't establish version control capabilities. The combination of A and B ensures that version control is properly configured in ADF and that a Git repository exists to track all changes, including the resources currently defined in the UX Authoring canvas.

Author: LeetQuiz Editorial Team