Microsoft Fabric workspaces contain a variety of artifacts, including Notebooks, scripts, and other important files that define the structure and data processing within our Data Lake solution.
Why Source Control is Important
Source code version control is an important feature of a high-quality deployment. When we implement source control within software development or data management solutions, we gain some important capabilities, including:
- The ability to quickly revert unintended or breaking changes to code.
- An infrastructure for enabling code review by other data engineers, data scientists and deployment engineers before committing to code deployment, for example using pull requests.
- The ability to control and automate the promotion of artifacts between development, test and production environments.
While source control systems were originally developed for software development, they are often used for data engineering and data science projects as well. Using source control systems, such as Git, we can actively manage the development and deployment processes for our data solutions and ultimately improve the quality and reliability of our solutions.
Fabric's Source Control Support
Fabric supports source control via its Git integration. At the time of this writing, Fabric supports using Azure DevOps as the Git provider for its integration.
Fabric/Git integration is configured at the Workspace level, and each workspace with Git integration will be synchronized with a specific folder within a DevOps Git Repository (the folder can be the root folder of the Git repository).
Fabric Artifacts Supported
As of this writing, Fabric will synchronize the following assets with the external Git repository:
- Lakehouse metadata
- Notebooks metadata and content
- Paginated reports
- Reports (except reports connected to semantic models hosted in Azure Analysis Services, SQL Server Analysis Services or reports exported by Power BI Desktop that depend on semantic models hosted in MyWorkspace).
- Semantic models (except push datasets, live connections, model v1, and semantic models created from the Data warehouse/Lakehouse.)
Configuring the Repository
The steps to create a new repository and integrate it with Fabric is best explained through a demo, so review the following embedded YouTube video for a complete walk-through!