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            Use Clustering on Structured Data

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            Use Clustering on Structured Data

            Use clustering models in Data 360 to automatically group data model object (DMO) records by shared characteristics. Run a predict job or batch data transform to assign new records to saved clusters, and use the results across Salesforce.

            Required Editions

            Available in: All Editions supported by Data 360. See Data 360 edition availability.
            User Permissions Needed
            Allow users to manage models in Einstein Studio (AI Models) Enables you to create, update, and delete models in the Data 360 AI Models tab.
            Permission sets
            Data Cloud Architect Admin-level access to all AI Models features, including the ability to create, update, delete, and activate models.
            Data Cloud User Restricted access to use a model, including getting predictions and improvements derived from a model.

            Before you begin:

            • Build and activate a clustering model in the AI Models tab in Data 360.
            • Make sure that you use a DMO with structured data.

            Tips:

            • Use scores to rank or filter records by confidence. If a record has a low cluster score, it can be a poor fit for its assigned cluster.
            • Cluster label names reflect what you set during model setup. To change labels, edit the clustering model and rerun the transform.

            Map Records to Clusters with a Predict Job

            Use a predict job to run inference and map new records to clusters in a DMO.

            1. From Data 360, go to the AI Models tab, and click the activated clustering model.
            2. On the Integrations tab, select Add Job. Predict Job Builder opens.
            3. Set the model inputs using a DMO, and map its fields to the model’s variables.
            4. Define the output DMO. Optionally, specify how many top contributors to include.
            5. Schedule a streaming or batch job.
            6. Save the job.
            7. Activate and run the predict job.

            Run Clustering with a Data Transform

            Use a batch data transform to apply cluster labels to new data in a DMO.

            Important
            Important

            Deleting the clustering model removes all downstream transform jobs. Before you delete the model, delete all associated transforms.

            1. From Data 360, go to the AI Models tab, and click the activated clustering model.
            2. On the Integrations tab, select Add Transform.
            3. In the transform setup, select the structured DMO that contains the records you want to assign to clusters.
            4. Map the DMO fields to the corresponding fields used during model training.
            5. Configure the output DMO settings.
              • DMO name: The name of the output DMO.
              • Cluster ID: The name for the cluster ID field (the API name is set automatically and you can't change it).
              • Cluster Label: A descriptive label that summarizes the records in the cluster.
            6. Configure up to 3 top contributors to include in the output.
            7. Activate and run the predict job.
            8. Save and run the transform.
             
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