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            Create a Search Index for Problem for IT Services

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            3. Agentforce IT Service

            Create a Search Index for Problem for IT Services

            Create a data stream from your Salesforce org, map the data to the appropriate data model, and then create a search index to make your problem data usable for AI features that use Data 360.

            Required Editions

            Available in: Lightning Experience
            Available in: Enterprise, and Unlimited Editions with Agentforce IT Service.
            User Permissions Needed
            To create search indexes: Data Cloud Admin

            Configure the Problem Data Stream

            Create a data stream to ingest your problem data from Salesforce into Data Cloud.

            1. From the App Launcher, find and select Data Cloud.
            2. Click the Data Streams tab.
            3. In the Data Stream window, click New.
            4. Under connected sources, select Salesforce CRM and click Next.
            5. Select the Salesforce org that contains your problem data.
            6. Click View Objects.
              A list of available Salesforce objects appears.
            7. Find and select the Problem object, and then click Next.
            8. On the problem details page:
              1. Select the object category as Others.
              2. Ensure all required fields are selected. By default, all fields are included.
            9. Click Next.
            10. Review the data stream details and click Deploy.
              After deployment, Data 360 creates a new data stream named Problem_Home.

            Map Data Stream Fields

            Map Problem record fields to the corresponding fields in the problem data model object (DMO). Mapping ensures that Data 360 correctly interprets your data.

            1. From the Data Streams tab, click the Peoblem_Home data stream you just created.
            2. On the data mapping card, click Start.
            3. On the data model entities card, click Select objects.
              In the data mapping interface, you see the source fields from Problem_Home on the left and the target fields in the data model on the right.
            4. Map the fields that are required for your processes. Map these recommended fields:
              • Problemid
              • ProblemNumber
              • SubjectDescription
              • Description
              • ProblemCategory
              • ProblemSubCateogory
              • ProblemPriority
              • ProblemStatusCategory
              • RootCauseSummaryText
              • OwnerId
              • CreatedDate
              • ProblemImpact
              • ProblemUrgency
              • ProblemStatus
              • ProblemResolutionStatus
              • ResolutionSummaryText
              • WorkaroundDescription
              • PermanentSolutionDescription
              • CommentText
            5. After you mapped all required fields, click Save & Close.
            6. Go to the data streams tab and monitor the Problem_Home data stream. Wait for the status to change to Active, which indicates that Data 360 ingested and mapped the data.

            Create the Search Index

            Create a search index to enable fast and efficient querying of your problem data for AI-driven features. You can use a preconfigured data kit for a quick setup or use the advanced setup for more control.

            1. In Data Cloud, go to the Search Index tab. If you don't see the search index tab, click More and then select it.
            2. Click New.
            3. In the new search index configuration window, choose your setup method:
              • From a Data Kit: For a streamlined setup, select From a Data Kit. Select IT Services Data Kit from the list, select the Problem index, and then click Next.
              • Advanced Setup: For manual control, select Advanced Setup and click Next.
            4. Select the Problem data model object.
            5. Click Next.
            6. In the chunking step:
              1. Click Manage Fields.
              2. Select the check boxes for the Subject and Description fields. These fields are used to create searchable text chunks.
              3. Click Save.
            7. Click Next.
            8. In the vectorization step, select the E5 Large V2 Embedding Model and click Next.
            9. Select a vectorization strategy based on your embedding model. This strategy determines how Data 360 measures your unstructured data for semantic relevance when building search results.
            10. In the fields for filtering step, drag the fields you want to use for filtering search results from the available fields list to the selected fields area. Add these recommended fields:
              • Status Category
              • Category
              • Root Cause Summary
              • Priority
              • Owner ID
              • Created Date
            11. Click Next.
            12. On the review and build step, review the complete configuration.
            13. Click Save to create and build the search index.
              After the search index is created and processed, you can view its configuration details and process history from the search index tab.
             
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