Data Prep for Data Collection

Data Prep is an Adobe Experience Platform service that allows you to map, transform, and validate data to and from Experience Data Model (XDM). When configuring a Platform-enabled datastream, you can use Data Prep capabilities to map your source data to XDM when sending it to the Platform Edge Network.


For comprehensive guidance on all Data Prep capabilities, including transformation functions for calculated fields, refer to the following documentation:

This guide covers how to map your data within the UI. To follow along with the steps, start the process of creating a datastream up to (and including) the basic configuration step.

For a quick demonstration of the Data Prep for Data Collection process, refer to the following video:

Select data

Select Save and Add Mapping after completing the basic configuration for a datastream, and the Select data step appears. From here, you must provide a sample JSON object that represents the structure of the data that you plan on sending to Platform.

To capture properties directly from your data layer, the JSON object must have a single root property data. The sub-properties of the data object should then be constructed in a way that maps to the data layer properties that you want to capture. Select the section below to view an example of a properly formatted JSON object with a data root.

 Sample JSON file with data root
  "data": {
    "eventMergeId": "cce1b53c-571f-4f36-b3c1-153d85be6602",
    "eventType": "view:load",
    "timestamp": "2021-09-30T14:50:09.604Z",
    "web": {
      "webPageDetails": {
        "siteSection": "Product section",
        "server": "",
        "name": "product home",
        "URL": ""
      "webReferrer": {
        "URL": "",
        "type": "external"
    "commerce": {
      "purchase": 1,
      "order": {
        "orderID": "1234"
    "product": [
        "productInfo": {
          "productID": "123"
        "productInfo": {
          "productID": "1234"
    "reservation": {
      "id": "anc45123xlm",
      "name": "Embassy Suits",
      "SKU": "12345-L",
      "skuVariant": "12345-LG-R",
      "priceTotal": "112.99",
      "currencyCode": "USD",
      "adults": 2,
      "children": 3,
      "productAddMethod": "PDP",
      "_namespace": {
        "test": 1,
        "priceTotal": "112.99",
        "category": "Overnight Stay"
      "freeCancellation": false,
      "cancellationFee": 20,
      "refundable": true

To capture properties from an XDM object data element, the same rules apply to the JSON object, but the root property must be keyed as xdm instead. Select the section below to view an example of a properly formatted JSON object with an xdm root.

 Sample JSON file with xdm root
  "xdm": {
    "environment": {
      "type": "browser",
      "browserDetails": {
        "userAgent": "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_7_5) AppleWebkit/537.36 (KHTML, like Gecko) Chrome/49.0.2623.112 Safari/537.36",
        "javaScriptEnabled": true,
        "javaScriptVersion": "1.8.5",
        "cookiesEnabled": true,
        "viewportHeight": 900,
        "viewportWidth": 1680,
        "javaEnabled": true
      "domain": "",
      "colorDepth": 24,
      "viewportHeight": 1050,
      "viewportWidth": 1680
    "device": {
      "screenHeight": 1050,
      "screenWidth": 1680

You can select the option to upload the object as a file, or paste the raw object into the provided textbox instead. If the JSON is valid, a preview schema is displayed in the right panel. Select Next to continue.

JSON sample of expected incoming data


The Mapping step appears, allowing you to map the fields in your source data to that of the target event schema in Platform. From here, you can configure the mapping in two ways:

Create a new mapping

To get started, select Add new mapping to create a new mapping row.

Adding a new mapping

Select the source icon (Source icon), and in the dialog that appears select the source field that you want to map in the provided canvas. Once you have chosen a field, use the Select button to continue.

Selecting the field to be mapped in the source schema

Next, select the schema icon (Schema icon) to open a similar dialog for the target event schema. Choose the field that you want to map the data to before confirming with Select.

Selecting the field to be mapped in the target schema

The mapping page reappears with the completed field mapping shown. The Mapping progress section updates to reflect the total number of fields that have been successfully mapped.

Field successfully mapped with progress reflected


If you want to map an array of objects (in the source field) to an array of different objects (in the target field), add [*] after the array name in the source and destination field paths, as shown below.

Array object mapping

Import existing mapping rules

If you have previously created a datastream, you can re-use its configured mapping rules for a new datastream.


Importing mapping rules from another datastream will overwrite any field mappings you might have added before the import.

To start, select Import Mapping.

Image showing the Import Mapping button being selected

In the dialog that appears, select the datastream whose mapping rules you want to import. Once the datastream is chosen, select Preview.

Image showing an existing datastream being selected


Datastreams can only be imported within the same sandbox. In other words, you cannot import a datastream from one sandbox to another.

The next screen shows a preview of the saved mapping rules for the selected datastream. Make sure that the displayed mappings are what you expect, and then select Import to confirm and add the mappings to the new datastream.

Image showing the mapping rules to be imported


If any source fields in the imported mapping rules are not included in the sample JSON data that you provided earlier, those field mappings will not be included in the import.

Complete the mapping

Continue following the above steps to map the rest of the fields to the target schema. While you do not have to map all available source fields, any fields in the target schema that are set as required must be mapped in order to complete this step. The Required fields counter indicates how many required fields are not yet mapped in the current configuration.

Once the required fields count reaches zero and you are satisfied with your mapping, select Save to finalize your changes.

Mapping complete

Next steps

This guide covered how to map your data to XDM when setting up a datastream in the UI. If you were following general datastreams tutorial, you can now return to the step on viewing datastream details.

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