--- schema_version: "1" id: 75280985d0c54f047d199f753365f935ea676c78e2a0e1b86b711c78321565a1 title: Map Model Variables collection: admin version: current locale: en-us portal_url: https://docs.salesforce.com/admin/current/en-us/analytics/264-0-0/bi_edd_model_deploy_map.md canonical_url: https://help.salesforce.com/s/articleView?id=analytics.bi_edd_model_deploy_map.htm&release=264.0.0&type=5 source_site: help.salesforce.com content_type: documentation content_hash: 3013c37a1aff7a1cee79345cfaab8358e01d49cb43de073bf9ae4e6c9770685d description: Define the mapping between variables in the model to fields in the Salesforce object or to columns in the supplemental dataset. products: - CRM Analytics - Cross Cloud release: "264" --- # Map Model Variables Define the mapping between variables in the model to fields in the Salesforce object or to columns in the supplemental dataset. ![Note](https://sf-zdocs-cdn-prod.zoominsoftware.com/tdta-analytics-bi-264-0-0-production-enus/ec791473-f5b4-4f64-a656-9104f455d966/images/icon_note.png) Note Einstein Discovery stories are now models. We wish we could snap our fingers to update the name everywhere, but you can expect to see the previous name in a few places until we replace it. ![Deploy Model page showing the mapping interface](https://sf-zdocs-cdn-prod.zoominsoftware.com/tdta-analytics-bi-264-0-0-production-enus/ec791473-f5b4-4f64-a656-9104f455d966/bi/images/bi/bi_edd_model_deploy_fields.png) 1. If you want to include external data or computed fields in queries associated with this model, click **Add Supplemental Dataset** and fill in the following fields. ![Deploy Model page showing the supplemental dataset settings](https://sf-zdocs-cdn-prod.zoominsoftware.com/tdta-analytics-bi-264-0-0-production-enus/ec791473-f5b4-4f64-a656-9104f455d966/bi/images/bi/bi_edd_model_deploy_fields_supplemental.png)
Field Description
Connected Salesforce Object Name of the selected Salesforce object. Read only.
Connected Salesforce Object ID Field

Name of the Object ID field in the selected Salesforce object. Einstein automatically selects a default field. If you want to change this setting, click the x and select a different field.

Note
Note Einstein displays object fields to which you have access. If you don't see the object ID field you expect, check the field-level security settings for your user account to ensure that you have at least read access to that field in the Salesforce object.
Supplemental Dataset

Name of the supplemental dataset that contains the additional data to use when scoring records.

Note
Note Adding a dataset uses only Salesforce sharing rules. Any sharing rules on the dataset are ignored.
  • Use supplemental datasets for predictive models that require information that’s not found in Salesforce objects.
    • External data. You can use data that’s stored outside of Salesforce for your model. For example, a model predicting likelihood to win an opportunity can use advertising history that’s stored in another system as an explanatory variable.
    • Data Prep datasets. You can use datasets created in Data Prep for your model. For example, a model that scores opportunities can use the calculated variable of task total which was created in a Data Prep recipe. Using a recipe, you can calculate and save the task total value in a supplemental CRM Analytics dataset. Then, when Einstein scores opportunity records, it retrieves this calculated value from the row of the supplemental dataset corresponding to the record in the Salesforce object.
      Note
      Note Predictions that connect to a dataset depend on the frequency with which the dataset is refreshed.
Supplemental Dataset Record ID Column Record ID field in the selected supplemental dataset that corresponds to the selected Object ID field in the Salesforce object.
2. For a field in the dataset, select its corresponding field in the Salesforce object. ![Note](https://sf-zdocs-cdn-prod.zoominsoftware.com/tdta-analytics-bi-264-0-0-production-enus/ec791473-f5b4-4f64-a656-9104f455d966/images/icon_note.png) Note - If you want to deploy this model using automated prediction fields (see [Display Einstein Predictions Using Automated Prediction Writeback](https://help.salesforce.com/s/articleView?id=analytics.bi_edd_prediction_automated.htm&release=264.0.0&type=5 "When automated prediction writeback fields are configured for a prediction definition that outputs a numerical prediction (regression) or score (binary classification), Einstein Discovery can save predictions directly to Salesforce records for use in reports and list views. Configure automated prediction writeback in Model Manager. After deployment, Einstein scores newly created or updated records in the Salesforce object and writes the score to the prediction field. Only the prediction is written, not the reasons for the prediction or the suggested ways in which to improve the prediction.")), you must map _all_ fields. - If you deploy this model without automated prediction fields, then you don’t need to map all fields. - If you want to use this model for the [prediction Transformation](https://help.salesforce.com/s/articleView?id=analytics.bi_integrate_prediction_transformation.htm&release=264.0.0&type=5 "The prediction transformation produces an Einstein Discovery prediction for a dataset. Einstein Discovery uses predictive analytics, which analyzes historical data (based on data mining, machine learning, and predictive statistical modeling) to identify patterns and predict future outcomes.") in CRM Analytics data flows, then you don’t need to map fields. | Field | Description | | --- | --- | | **Model Variable** | Name of the variable in the model. | | **Object Field** | Name of the field in the Salesforce object. | | **Dataset Column** | Name of the corresponding column in the supplemental dataset, if applicable. | 3. If the model is configured with a projected prediction, be sure to map the projected prediction variable, and map the Record ID variable to the unique identifier column in the trending dataset. ![Deploy Model page showing the mapping interface](https://sf-zdocs-cdn-prod.zoominsoftware.com/tdta-analytics-bi-264-0-0-production-enus/ec791473-f5b4-4f64-a656-9104f455d966/bi/images/bi/bi_edd_model_deploy_map_projected.png) To learn more, see [Configure Projected Predictions](https://help.salesforce.com/s/articleView?id=analytics.bi_edd_story_number_projected_predictions.htm&release=264.0.0&type=5 "Einstein Discovery allows you to provide trending data for numeric variables that factor into your predictions to make them more accurate. For example, you predict opportunity win/loss based on expected price fluctuations for raw materials. To factor price into your predicted outcome, use the Projected Predictions transformation and provide a dataset that projects the expected price for raw materials on the close date."). 4. Click **Next**.