You want to save the enriched metadata (like extracted key phrases and entities) generated by your Azure AI Search skillset so that data analysts can query it using Power BI and Synapse Analytics. How should you configure the skillset?

Direct Answer (Verified)Reviewed by Sunny (Senior Cloud Engineer)

Correct Answer: Add a Knowledge Store definition referencing an Azure Storage account to save projections as tables or blobs.

A Knowledge Store is a feature of Azure AI Search that allows you to save enriched content (projections) generated by skillsets into Azure Table storage, Blob storage, or file shar...

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Real Exam ScenarioAzure AI Search (Knowledge Store)

You want to save the enriched metadata (like extracted key phrases and entities) generated by your Azure AI Search skillset so that data analysts can query it using Power BI and Synapse Analytics. How should you configure the skillset?

โœ“ Correct Answer & ExplanationAzure AI Search (Knowledge Store)

Correct Answer

Add a Knowledge Store definition referencing an Azure Storage account to save projections as tables or blobs.

Why This Answer Is Correct

A Knowledge Store is a feature of Azure AI Search that allows you to save enriched content (projections) generated by skillsets into Azure Table storage, Blob storage, or file shares. This enables downstream analysis without re-running the search indexing pipeline.

๐Ÿ“š What This Question Tests

This question evaluates your knowledge of Azure AI Search (Knowledge Store) โ€” a core concept tested in Microsoft Certified: Azure AI Engineer Associate (AI-102). Understanding Azure AI Search (Knowledge Store) is essential for designing scalable, secure, and cost-effective cloud architectures. Mastery of this topic will help you answer scenario-based questions confidently on exam day.