Microsoft Azure AI Engineer Associate AI-102 Practice Question
An Azure AI Content Understanding pipeline must enrich PDF, PNG, MP4, and WAV files dropped into an Azure Blob Storage container, then push extracted text, speech, and video thumbnails into an Azure AI Search index. Before a single skillset can ingest all four formats, which prerequisite must you satisfy?
Enable the Azure Blob Storage change-feed on the container that receives the files.
Deploy a custom Form Recognizer model in the same resource group as the AI Search service.
Create and associate an Azure AI Video Indexer (ARM-based) account with a valid API key and location.
Install the Azure Cognitive Search optional Blob Storage media extension on the search service.
Azure AI Search indexers natively crack text-based formats such as PDF and can call built-in cognitive skills for images. However, audio and video enrichment relies on the Azure Video Indexer cognitive skill, which in turn requires that a Video Indexer resource be connected to your Azure subscription through an ARM-based account with an API key. Without creating and linking that account, the skill cannot extract spoken words or thumbnails, so MP4 and WAV files will fail. Enabling blob change feed, installing extensions, or deploying a Form Recognizer model does not meet this dependency.
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What is Azure Video Indexer and what role does it play in content enrichment pipelines?
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How does Azure AI Search integrate with different file formats like PDF, PNG, MP4, and WAV?
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Why is enabling Azure Blob Storage change-feed not sufficient for this pipeline requirement?
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Microsoft Azure AI Engineer Associate AI-102
Implement knowledge mining and information extraction solutions
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