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Mapping fields for the POST method when creating a data object

Keep sensitive data private by connecting to your system of record using the POST method.

  1. Click Add sample request.

  2. Optional:

    To import key value pairs from a file, click Choose File.

    Each key value pair must have a colon between the key and the value and be separated by a new line, for example:

    amount: 285

    currency: usd

    1. Navigate to the file you want to import and click Open.

    2. Edit the fields as necessary.

  3. Click +Add parameter to add key value pairs to include in the request body.

  4. Click Map request.

  5. To add a field to the data view, click Add new.

    1. In the Map to field, enter the name of the field.

    2. Select the type of data that the field contains.

  6. Click Initialize call.

    The connector parameters are on the left and the data page parameters are on the right. The top-level JSON element determines the structure of the data page - a list page if it's an array, or a single page if it's an object..
  7. Choose whether to use live data or data from a JSON file to create the data object.

    • To use data from your system of record, select Live response.
    • To use data from a JSON file, click Sample JSON Add sample response . Follow the prompts to upload a file or paste in sample JSON and click Submit.
  8. Create properties in the data object and map the response fields to your data view.

    1. Select the fields that you want to include in the data object and map them to your data view by using the following options:

      • To add the field to the data object, click Add new. You can change the field name and its type.
      • To add all of the fields from the REST response to the data object using the same field names, click Add all. To change the name and the data object, click the name. To remove a field mapping, click the name and click the delete icon.
      • To remove all of the fields from the data object, click Clear all.
  9. Click Next

  10. Click Submit.

  11. Click Save.

Prepare you data for production by configuring the environment settings. For more information, see Preparing your data for production.

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