Data Prep UI Guide
Read this guide to learn how to use data prep mapping functions in the Adobe Experience Platform user interface to map CSV files to an Experience Data Model (XDM) schema.
Get Started
This tutorial requires a working understanding of the following Platform components:
-
Experience Data Model (XDM) System: The standardized framework by which Platform organizes customer experience data.
- Basics of schema composition: Learn about the basic building blocks of XDM schemas, including key principles and best practices in schema composition.
- Schema Editor tutorial: Learn how to create custom schemas using the Schema Editor UI.
-
Identity Service: Gain a better view of individual customers and their behavior by bridging identities across devices and systems.
-
Real-Time Customer Profile: Provides a unified, real-time consumer profile based on aggregated data from multiple sources.
-
Sources: Experience Platform allows data to be ingested from various sources while providing you with the ability to structure, label, and enhance incoming data using Platform services.
Access the mapping interface in the UI
You can access the mapping interface in the UI through two different pathways.
- In the Experience Platform UI, select Workflows from the left-navigation and then select Map CSV to XDM schema. Next, provide your dataflow details and select the data that you want to ingest. When finished, you are taken to the mapping interface where you can configure mapping between your source data and an XDM schema.
- You can also access the mapping interface through the sources workspace.
Map CSV files into an XDM schema
Use the mapping interface and the comprehensive toolset that it provides to successfully map data fields from your source schema to their appropriate target XDM fields in the target schema.
Understanding the mapping interface mapping-interface
Refer to the dashboard at the top of the interface for information on the health of your mapping fields within the context of the ingestion workflow. The dashboard displays the following details regarding your mapping fields:
Next, you can use the options listed in the header to better interact or filter through your mapping fields.
Select All fields to view a dropdown menu of options to filter your mappings by. The available filtering options include:
- Required fields: Filters the interface to display only fields required to complete the workflow.
- Identity fields: Filters the interface to display only fields marked as identities.
- Mapped fields: Filters the interface to display only fields that have already been mapped.
- Unmapped fields: Filters the interface to display only fields that have yet to be mapped.
- Fields with errors: Filters the interface to display only fields that have errors.
Add a new field type add-a-new-field-type
You can add a new mapping field or a calculated field by selecting New field type.
New mapping field
To add a new mapping field, select New field type and then select Add new field from the dropdown menu that appears.
Next, select the source field you would like to add from the source schema tree that appears and then select Select.
The mapping interface updates with the source field you selected and an empty target field. Select Map target field to start mapping the new source field to its appropriate target XDM field.
An interactive target schema tree appears, allowing you to manually traverse through the target schema and find the appropriate target XDM field for your source field.
Calculated fields calculated-fields
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. Calculated fields have a maximum length of 4096 characters.
To create a calculated field, select New field type and then select Add calculated field
The Create calculated field window appears. Use the interface to input your calculated fields and refer to the dialog box on the left for supported fields, functions, and operators.
You can manually add fields, functions, and operators using the expression editor at the center. Select the editor to start creating an expression. Once you are finished, select Save to proceed.
Import mapping import-mapping
You can reduce the manual configuration time of your data ingestion process and limit mistakes by using the import mapping functionality of data prep. You can import mappings from an existing flow or from an exported file.
If you have several dataflows based on similar source files and target schemas, then you can import existing mapping and reuse them for new dataflows.
To import mapping from an existing dataflow, select Import mappings and then select Import mapping from flow.
Next, use the pop-up window to locate the dataflow whose mapping you want to import. During this step, you can also use the search function to isolate a specific dataflow and retrieve it’s mappings. When finished, select Select.
In some cases, you may need to implement a large number of mappings for your data. You can do this manually with the mapping interface, but you can also export your mapping template and configure your mappings on an offline spreadsheet to save time and avoid user timeouts on Experience Platform.
To import mapping from an exported file, select Import mappings and then select Import mapping from file.
Next, use Upload template window to download a CSV copy of your mappings. You can then configure your mappings locally on your device, using any software that support editing CSV file types. During this step, you must ensure that you are using only the fields that are provided in your source file and target schema.
accordion |
---|
Select to view an example of an exported mapping file |
![]() |
When finished, select Upload file and select the updated csv file of your mappings. Allow for a brief moment for the system to process, and then select Done.
With your mappings complete, you can now select Finish and proceed to the next step to complete your dataflow.
Next steps
You now can successfully map a CSV file to a target XDM schema using the mapping interface in the Experience Platform UI. For more information, read the following documents: