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Map a CSV file to an existing XDM schema

In order to ingest CSV data into �۶���Ƶ Experience Platform, the data must be mapped to an Experience Data Model (XDM) schema. This tutorial covers how to map a CSV file to an XDM schema using the Platform user interface.

Getting started

This tutorial requires a working understanding of the following components of Platform:

This tutorial also requires that you have already created a dataset to ingest your CSV data into. For steps on creating a dataset in the UI, see the data ingest tutorial.

Choose a destination

Log in to and then select Workflows from the left navigation bar to access the Workflows workspace.

From the Workflows screen, select Map CSV to XDM schema under the Data ingestion section and then select Launch.

The Map CSV to XDM schema workflow appears, starting on the Destination step. Choose a dataset for inbound data to be ingested into. You can either use an existing dataset or create a new one.

Use an existing dataset

To ingest your CSV data into an existing dataset, select Use existing dataset. You can either retrieve an existing dataset using the search function or by scrolling through the list of existing datasets in the panel.

To ingest your CSV data into a new dataset, select Create new dataset and enter a name and description for the dataset in the fields provided. Select a schema by using either the search function or by scrolling through the list of schemas provided. Select Next to proceed.

Add data

The Add data step appears. Drag-and-drop your CSV file into the space provided, or select Choose files to manually input your CSV file.

The Sample data section appears once the file is uploaded, showing the first ten rows of data. Once you have confirmed that the data has uploaded as expected, select Next.

Map CSV fields to XDM schema fields

The Mapping step appears. The columns of the CSV file are listed under Source Field, with their corresponding XDM schema fields listed under Target Field.

Platform automatically provides intelligent recommendations for auto-mapped fields based on the target schema or dataset that you selected. You can manually adjust mapping rules to suit your use cases.

To accept all the auto-generating mapping values, select the checkbox labelled “Accept all target fields”.

Sometimes, more than one recommendation is available for the source schema. When this happens, the mapping card displays the most prominent recommendation, followed by a blue circle that contains the number of additional recommendations available. Selecting the light bulb icon will show a list of the additional recommendations. You can choose one of the alternate recommendations by selecting the checkbox next to the recommendation you want to map to instead.

Alternatively, you can choose to manually map your source schema to your target schema. Hover over the source schema you want to map, then select the plus icon.

The Map source to target field popover appears. From here, you can select which field you want to be mapped, followed by Save to add your new mapping.

If you want to remove one of the mappings, hover over that mapping, then select the minus icon.

Add calculated field add-calculated-field

Calculated fields allow for values to be created based on the attributes in the input schema. These values can then be assigned to attributes in the target schema and be provided a name and description to allow for easier reference.

Select the Add calculated field button to proceed.

The Create calculated field panel appears. The left dialog box contains the fields, functions, and operators supported in calculated fields. Select one of the tabs to start adding functions, fields, or operators to the expression editor.

You can manually add fields, functions, and operators using the expression editor at the center. Select the editor to start creating an expression.

Select Save to proceed.

The mapping screen reappears with your newly created source field. Apply the appropriate corresponding target field and select Finish to complete the mapping.

Monitor data ingestion

Once your CSV file is mapped and created, you can monitor the data that is being ingested through it. For more information on monitoring data ingestion, see the tutorial on monitoring data ingestion.

Next steps

By following this tutorial, you have successfully mapped a flat CSV file to an XDM schema and ingested it into Platform. This data can now be used by downstream Platform services such as Real-Time Customer Profile. See the overview for Real-Time Customer Profile for more information.