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AI-900 Practice Question: Describe features of computer vision workloads on Azure

What is 'video indexer' (Azure Video Indexer) and what insights does it extract?

⚠ Common exam trap

It's easy for candidates to confuse Azure Video Indexer with a storage or database optimization tool, because the word 'indexer' misleadingly suggests indexing for performance, whereas it is actually an AI-based video analysis service for extracting metadata and insights.

Answer choices

Why each option matters

Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.

Correct answer & explanation

A service that extracts transcripts, faces, speakers, topics, and scenes from video content

Azure Video Indexer is a cloud-based service that uses AI to analyze video and audio content. It extracts rich insights such as transcripts (speech-to-text), identified faces, speaker diarization, topics, scenes, and even sentiment, making it a comprehensive media intelligence tool rather than a storage or indexing utility.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • A tool that compresses videos to reduce storage costs in Azure Blob Storage

    Why it's wrong here

    This describes a video encoding or transcoding task that reduces file size for storage optimization, typically handled by Media Services, not Video Indexer. Video Indexer performs no compression or resizing; it leaves the original video untouched and instead analyzes its content to create a JSON metadata output. The goal of Video Indexer is to enrich video with AI-generated insights, not to change its storage footprint.

  • A service that extracts transcripts, faces, speakers, topics, and scenes from video content

    Why this is correct

    Video Indexer is a cloud service that uses pre-built AI models to analyze both audio and video, extracting a wide range of insights. These include speech-to-text transcripts with timestamps, face detection and identification, speaker diarization, topic extraction, and scene segmentation. The output is a structured, searchable metadata file that enables content discovery, accessibility, and automated metadata generation for media workflows.

  • A database index that speeds up queries on video metadata tables

    Why it's wrong here

    This is a database-level performance optimization that speeds up queries on structured metadata tables. Video Indexer does produce metadata, but it is not a database index; rather, it is a cloud service that uses AI models to extract insights like transcripts, faces, and speakers from video. The extracted metadata can be stored and indexed, but the service itself is the analyzer, not the index.

  • A tool for creating video presentations from a series of images and text

    Why it's wrong here

    This describes a media authoring or presentation tool, not an AI-powered analysis service. Video Indexer consumes existing video files and applies computer vision, speech, and natural language models to generate insights; it does not generate or edit video content from still images and text. The misconception stems from both involving video, but creation and analysis are distinct workloads.

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Written by Johnson Ajibi, MSc IT Security

Senior Network & Security Engineer · founder of Courseiva

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