In Azure Cognitive Search, a knowledge store is an optional capability that allows you to persist the enriched data from a skillset (enrichment pipeline) into an Azure Storage account. This is often used when you want to further analyze or visualize enriched content, e.g., sentiment analysis results from social media posts.

When defining a knowledge store, you need:

storageConnectionString

This is required so the enrichment pipeline can connect to your Azure Storage account.

Without it, the knowledge store cannot persist any data.

storageContainer

This specifies the container in Blob Storage where enriched documents or projections will be stored.

This allows you to persist the original documents and enriched outputs such as sentiment analysis scores.

Other options (not correct in this case):

tables → This is a projection type used within a knowledge store to structure output in Table Storage, but it’s not required in the definition itself.

files → Another projection type for storing enriched documents as files in Blob Storage, but again, not a required field in the definition itself.

objects → A projection type used for representing enriched documents as JSON objects in Blob Storage.

Thus, while tables, files, and objects are used inside projections within a knowledge store, the definition itself always requires a storage connection string and storage container.

Correct Answer:

A. storageContainer

C. storageConnectionString

Knowledge store in Azure Cognitive Search

How to define a knowledge store

Microsoft References