Persist enriched data in a knowledge store - Learn
docs.microsoft.com/en-us/learn/modules/intro-to-azure-search/2e-understand-knowledge-store
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A knowledge store is persistent storage of enriched content.
Persist enriched data in a knowledge store
or example, you may want to save the results of an AI skillset that generates captions from images.
The outcome can be a search index, or projections in a knowledge store
derived from the same inputs, but resulting in output that is structured, stored, and used in different applications.
The two outputs, search index and knowledge store, are mutually exclusive products of the same pipeline
A knowledge store can contain one or more of three types of projection of the extracted data:
Table projections are used to structure the extracted data in a relational schema for querying and visualization
Object projections are JSON documents that represent each data entity
File projections are used to store extracted images in JPG format
skillsets move a document through a sequence of enrichments that invoke transformations,
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