Create a dataset using API
Now create the Luma CRM Dataset
using the API.
Luma CRM Dataset
in the user interface that’s fine. Name it Luma CRM Dataset
and use the Luma CRM Schema
.Get the id of the schema to be used in the dataset
First we need to get the $id
of the Luma CRM Schema
:
- Open Postman
- If you don’t have an access token, open the request OAuth: Request Access Token and select Send to request a new access token, just like you did in the Postman lesson.
- Open the request Schema Registry API > Schemas > Retrieve a list of schemas within the specified container.
- Select the Send button
- You should get a 200 response
- Look in the response for the
Luma CRM Schema
item and copy the$id
value
Create the dataset
Now you can create the dataset:
-
Download Catalog Service API.postman_collection.json to your
Luma Tutorial Assets
folder. -
Import the collection into Postman
-
Select the request Catalog Service API > Datasets > Create a new dataset.
-
Paste the following as the Body of the request, replacing the id value with your own:
-
Select the Send button
-
You should get a 201 Created response containing the id of your new dataset!
400: There was a problem retrieving xdm schema
. Make sure you have replaced the id in the sample above with the id of your ownLuma CRM Schema
- No auth token: Run the OAuth: Request Access Token request to generate a new token
401: Not Authorized to PUT/POST/PATCH/DELETE for this path : /global/schemas/
: Update the CONTAINER_ID environment variable fromglobal
totenant
403: PALM Access Denied. POST access is denied for this resource from access control
: Verify your user permissions in the Admin Console
You can go back to the Datasets screen in the Platform user interface, you can verify the successful creation of all five datasets!
Additional Resources
Now that all of our schemas, identities, and datasets are in place, we can enable them for Real-Time Customer Profile.
Experience Platform
- Data Architect and Engineer Tutorial
- 1. Configure permissions
- 2. Create a sandbox
- 3. Set up Developer Console and Postman
- 4. Model data in schemas
- 5. Map identities
- 6. Create datasets
- 7. Enable profiles
- 8. Subscribe to data ingestion events
- 9. Ingest batch data
- 10. Ingest streaming data
- 11. Create merge policies
- 12. Apply data governance framework
- 13. Run queries
- 14. Build segments
- Conclusion