Maintaining Data Pipelines with Version Control and Git
Explore how to maintain data pipelines in Azure Data Factory using Git for version control. Understand how to connect ADF to GitHub, manage branches, and use CI/CD to ensure consistent, collaborative pipeline development. This lesson equips you to track changes, revert versions, and improve data pipeline reliability.
Maintaining data pipelines can be a daunting task, especially when multiple developers are working on the same pipeline. Version control is an essential tool for managing the pipeline’s code, configuration, and metadata. In this lesson, we’ll discuss how to maintain data pipelines with version control in Azure Data Factory and perform our version control activities using GitHub.
Version control in data pipelines
Version control, in the context of data pipelines, is a systematic approach to managing and tracking changes to the configuration, code, and definitions of data pipelines over time. It ensures that every modification to the pipeline is documented, allowing developers to view and revert back to previous versions if needed. By maintaining data pipelines through version control, teams can collaborate efficiently, easily track changes made by different members, and avoid conflicts during integration. This practice establishes a historical record of pipeline changes, facilitating effective troubleshooting and debugging when issues arise. ...