Tutorial: Ingest data into a Warehouse in Microsoft Fabric

Applies to: Warehouse in Microsoft Fabric

Now that you have created a Warehouse in Microsoft Fabric, you can ingest data into that warehouse.

Ingest data

  1. From the Build a warehouse landing page, select Data Warehouse Tutorial in the navigation menu to return to the workspace item list.

    Screenshot of the navigation menu, showing where to select Data Warehouse Tutorial.

  2. Select New > More options to display a full list of available items.

  3. In the Data Factory section, select Data pipeline.

    Screenshot of the data pipeline section, showing where to select Data pipeline.

  4. On the New pipeline dialog, enter Load Customer Data as the name.

    Screenshot of the New pipeline dialog box, showing where to enter the name and select Create.

  5. Select Create.

  6. Select Add pipeline activity from the Start building your data pipeline landing page.

    Screenshot of the Start building your pipeline screen, showing where to select Add pipeline activity.

  7. Select Copy data from the Move & transform section.

    Screenshot of the Move and transform section, showing where to select Copy data.

  8. If necessary, select the newly created Copy data activity from the design canvas and follow the next steps to configure it.

  9. On the General page, for Name, enter CD Load dimension_customer.

    Screenshot of the General tab, showing where to enter the copy activity name.

  10. On the Source page, select External for the Data store type.

  11. Next to the Connection box, select New to create a new connection.

    Screenshot of the Source tab, showing where to select External and New.

  12. On the New connection page, select Azure Blob Storage from the list of connection options.

    Screenshot of the Azure Blob Storage option.

  13. Select Continue.

  14. On the Connection settings page, configure the settings as follows:

    1. In the Account name or URL, enter https://azuresynapsestorage.blob.core.windows.net/sampledata/.

    2. In the Connection credentials section, select Create new connection in the dropdown list for the Connection.

    3. For Connection name, enter Wide World Importers Public Sample.

    4. Set the Authentication kind to Anonymous.

    Screenshot of the Connections settings screen with the Account name and Connection credentials fields filled in as directed in the previous steps.

  15. Select Create.

  16. Change the remaining settings on the Source page of the copy activity as follows, to reach the .parquet files in https://azuresynapsestorage.blob.core.windows.net/sampledata/WideWorldImportersDW/parquet/full/dimension_customer/*.parquet:

    1. In the File path text boxes, provide:

      1. Container: sampledata

      2. File path - Directory: WideWorldImportersDW/tables

      3. File path - File name: dimension_customer.parquet

    2. In the File format drop-down, choose Parquet.

  17. Select Preview data next to the File path setting to ensure there are no errors.

    Screenshot of the Source tab, showing where to change the file path and format details, and select Preview data.

  18. On the Destination page, select Workspace for the Data store type.

  19. Select Data Warehouse for the Workspace data store type.

  20. In the Data Warehouse dropdown, select WideWorldImporters from the list.

  21. Next to the Table option configuration setting, select the Auto create table radio button.

  22. The dropdown menu next to the Table configuration setting will automatically change to two text boxes.

  23. In the first box next to the Table setting, enter dbo.

  24. In the second box next to the Table setting, enter dimension_customer.

    Screenshot of the Destination tab, showing where to enter and select the details specified in the previous steps.

  25. From the ribbon, select Run.

  26. Select Save and run from the dialog box. The pipeline to load the dimension_customer table with start.

  27. Monitor the copy activity's progress on the Output page and wait for it to complete.

    Screenshot of the Output page, showing what a successful run looks like.

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