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Data factory is one of the best at combining the user-friendliness of a drag and drop tool w/ the versioning and automation of a code based tool.
One of the best features of data factory is the ability to connect directly to the get provider of your choice.
In this video we will see how this process actually works in Data Factory.
More about Source Control on Data Factory:
By default, the Azure Data Factory user interface experience (UX) authors directly against the data factory service. This experience has the following limitations:
- The Data Factory service doesn't include a repository for storing the JSON entities for your changes. The only way to save changes is via the Publish All button and all changes are published directly to the data factory service.
- The Data Factory service isn't optimized for collaboration and version control.
- The Azure Resource Manager template required to deploy Data Factory itself is not included.
To provide a better authoring experience, Azure Data Factory allows you to configure a Git repository with either Azure Repos or GitHub. Git is a version control system that allows for easier change tracking and collaboration.
Timestamps:
0:00 - Intro
0:26 - Create New Repo
1:20 - Configure Git
3:18 - Review Updated Repo
4:02 - Data Factory Workflow
6:56 - Live Mode Setting
Title & Tags:
How to Use GIT and GitHub on Azure Data Factory | Azure Tutorial for Beginners
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