dataflows-authoring-cli

You can create and update Microsoft Fabric Dataflows Gen2 by using the Fabric REST API to manage base64-encoded definitions, bind connections, configure output destinations, and verify refresh execution. This workflow handles full-definition replacement and long-running operations.

Yes, you can preview Power Query M mashup logic before saving a Fabric dataflow. The preview loop validates candidate mashup logic early to catch syntax, schema, and credential issues before committing definition updates to the workspace.

Automate Fabric dataflow refresh and connection binding by using Azure CLI, jq, and curl to interact with the Fabric REST API. This approach handles ClusterId resolution, composite connection IDs, refresh execution, and refresh verification for production workflows.

Yes, you need Azure CLI, jq, curl, and base64 handling to manage Fabric dataflow definitions. These tools are required to interact with the Fabric REST API, process base64-encoded definition parts, and handle long-running operations.

Yes, this approach supports configuring output destinations for Lakehouse, Warehouse, Azure Data Explorer, and Azure SQL targets. Destination publishing is handled as part of the end-to-end dataflow authoring workflow.

Updating a Fabric dataflow requires handling base64-encoded parts because the Fabric REST API transmits full definition replacements in base64 format. This ensures safe transport of Power Query M mashup logic and connection bindings during operations.