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            Create a Search Index Configuration from a Data Kit

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            Create a Search Index Configuration from a Data Kit

            After you have deployed your data kit in Data 360, you can create a new search index configuration from a index it contains.

            Required Editions

            Available in: All Editions supported by Data 360. See Data 360 edition availability.
            User Permissions Needed
            To create a search index configuration:

            Permission set:

            • Data Cloud Architect

            If the Object API name referenced in the data kit is available in the org where you create the search index, that object is automatically selected. If there’s no match for that Object API name, no object is selected. You can change this selection and choose a different object.

            1. From App Launcher, select Data Cloud.
            2. Click Search Index > New.
            3. Click Data Kit Setup.
            4. Select a search index from your data kit.
            5. On the Select Source DMO page, select a data space and an object.
              A search index configuration is created for each object that you select. You can’t select an object that has mappings from one or more external data lake objects.
            6. Click Next.
            7. If your search index is on a DMO, on the Chunking page, select fields to chunk and the chunking strategy.
              1. To add or remove fields, click Manage Fields and save your work.
              2. (Optional) Update the chunking strategy and modify the settings.
              3. Click Next.
            8. If your search index is on a UDMO, on the Chunking page, add a file extension or set a chunking strategy based on the file type.
              1. To add a file extension for a new file type, click Add File Extension.
              2. (Optional) Update the chunking strategy and modify the settings for an existing file type.
              3. Click Next.
            9. On the Vectorization page, from the dropdown list, select an embedding model and then click Next.
              The model determines how Data 360 measures your unstructured data objects for semantic relevance when building search results.
            10. Click Next.
            11. On the Fields for Filtering page, optionally add fields from the source object or related objects to provide more ways to filter a search. You can select up to ten filter fields.

              Data 360 picks up the pre-filter fields when you generate vector embeddings. If you change the values in those pre-filter fields, Data 360 picks them up when you generate or refresh those vector embeddings. The cardinality of object relationship between the source object and the related object must be either 1:1 or N:1.

              For example, if the indexed unstructured data includes case conversation transcripts, filtering on the Status field in the Case object can improve the relevance of semantic search results when searching the conversation transcripts.

            12. Click Next.
            13. Review the configuration and the target data model objects, and click Save.
             
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