Replace a Data Set in a Project

You can replace a data set by re-mapping columns used in a project to columns from a different data set.

As part of replacing a data set, you can review and re-map only those columns that are used in the project and replace them with columns of the same data type in the replacement data set. For example, you can replace a test data set with a production data set, or use a project as a template in which you can replace the data but maintain the added structures, visualizations, and calculations.
The Replace Data Set option is available for projects using multiple data sets that aren't joined.
  1. Create or open the project where you want to replace the data set.
    Confirm that you’re working in the Visualize canvas.
  2. In the Data Panel pane, right-click the data set and select Replace Data Set.
  3. In the Replace Data Set dialog, perform the following tasks:
    • Select the data set that replaces the existing data set in the project and click Select.

    • Review the mapping of the data between the existing and the new data sets in the data-mapping table. The data-mapping table includes all the data elements used in the project’s visualizations, calculations, and filters. The data elements with similar type and names in the two data sets are automatically mapped. In the table, based on data types, the data elements are grouped and sorted alphabetically.

    • In the new data set column, click the drop-down arrow in a cell and select a specific data element to adjust the mapping of the data.

      • Only data elements of the same type are displayed in the data element selection dialog.

      • You can navigate back to select a different data set.

  4. Click Replace.

The new data set replaces the existing data set in the project. You see a notification if you’ve selected a data set that is joined to other data sets in the project. Review and adjust the joins in the project’s Data Diagram.

In the data-mapping table based on the selection, the data is updated throughout the project. For example, if you map a data element to None, the specific data is removed from the visualizations, calculations, and filters.