Visual authoring in Azure Data Factory

The Azure Data Factory user interface experience (UX) lets you visually author and deploy resources for your data factory without having to write any code. You can drag activities to a pipeline canvas, perform test runs, debug iteratively, and deploy and monitor your pipeline runs.

Currently, the Azure Data Factory UX is only supported in Microsoft Edge and Google Chrome.

Authoring canvas

To open the authoring canvas, click on the pencil icon.

Authoring Canvas

Here, you will author the pipelines, activities, datasets, linked services, data flows, triggers, and integration runtimes that comprise your factory. To get started building a pipeline using the authoring canvas, see Copy data using the copy Activity.

The default visual authoring experience is directly working with the Data Factory service. Azure Repos Git or GitHub integration is also supported to allow source control and collaboration for work on your data factory pipelines. To learn more about the differences between these authoring experiences, see Source control in Azure Data Factory.

Expressions and functions

Expressions and functions can be used instead of static values to specify many properties in Azure Data Factory.

To specify an expression for a property value, select Add Dynamic Content or click Alt + P while focusing on the field.

Add Dynamic Content

This opens the Data Factory Expression Builder where you can build expressions from supported system variables, activity output, functions, and user-specified variables or parameters.

Expression builder

For information about the expression language, see Expressions and functions in Azure Data Factory.

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Next steps

To learn more about monitoring and managing pipelines, see Monitor and manage pipelines programmatically.