Set Up Your Data in SageMaker

Access Salesforce data from an Amazon SageMaker notebook using the Data 360 Python connector. The intuitive interface lets you quickly execute run queries and extract the data that you need.

1. 

   Important Creating connected apps is restricted as of Spring ‘26. You can continue to use existing connected apps during and after Spring ‘26. However, we recommend using external client apps instead. If you must continue creating connected apps, contact Salesforce Support.

   See New connected apps can no longer be created in Spring ‘26 for more details.

   In your SageMaker notebook, install the Python connector. The connector enables you to access Data 360 objects and ingest Salesforce data into SageMaker.
2. As part of the Python connector configuration, create an external client app or connected app.
3. Authenticate to securely access data using one of these methods.
   • Key-based
   • JWT
4. In Data 360, connect to your Salesforce data source to query the dataset. For example, to get email engagement data, access the Email Engagement object in Marketing Cloud Engagement.
5. To use the inferences in Data 360, upload the Python file to your notebook.
6. To get the model endpoint, go to the SageMaker dashboard in the Inferences section, and go to Endpoints. Note the URL as you need these details to connect your model with Salesforce.