Loading
Salesforce now sends email only from verified domains. Read More
About Salesforce Data 360
Table of Contents
Select Filters

          No results
          No results
          Here are some search tips

          Check the spelling of your keywords.
          Use more general search terms.
          Select fewer filters to broaden your search.

          Search all of Salesforce Help
          Connect a Databricks Model

          Connect a Databricks Model

          To consume predictions in Salesforce, connect your Databricks model with Data 360 and define the prediction criteria for your use case.

          Gather information about your model endpoint and the authentication details.

          1. In AI Models (formerly Einstein Studio), on the Predictive tab, click Add Predictive Model.
            Model Builder with a view of the SageMaker model type.
          2. To choose your model type, click Connect a Databricks model. Then click Next.
            Model Builder view that displays tiles which enable you to connect to different models.
          3. To connect the endpoint and access your model inferences, specify these details. Then click Next.
            • Name—Endpoint name
            • URL—Endpoint URL
            • Authentication—Key-based and JWT (API gateway required for both)
            • Auth Header—Authorization header
            • Secret Key—Bearer <personal access token>
            • Request Format—The format for requesting data from the application or server
              • DataFrame split
            • Response Format—The format for providing data from a server response.
              • JSON
          4. To add schema, click Enter the inputs and outputs.
            Model Builder view that displays your model schema. You add your inputs and outputs here.
            1. To add inputs (variables) that can impact your prediction, click Add Input. Then specify a name, an API name, and select the data type. Save your work as you add the inputs.
            2. To add your outputs, click Add Output. Then specify a name, an API name, a data type, and the JSON Key in a format similar to “$.predictions”. Save your work as you add the outputs.
              Important
              Important You must position the inputs in the order that matches your Databricks Select Query. To move an input, drag it to the preferred position in the Inputs section.
          5. Click Next.
          6. Review your model settings.
          7. To update your model settings, click the section where you want to make changes. Then navigate through the flow to review all settings.
          8. If you’re satisfied with your settings, click Save.
          9. Name your model and click Save & Connect. After the model is connected, you can find it on the model list view on the Predictive Models tab.
          10. To view your model details, click the model. You can activate, edit, or delete a model on this page.
          11. After the model is active, go to the Usage tab to create prediction jobs to consume your predictions.
          12. If you created a batch prediction, click Run to refresh your prediction scores.
            Note
            Note With streaming predictions, new inferences are initiated only when there’s a change in the input on your Data Model Object (DMO).
           
          Loading
          Salesforce Help | Article