- A
Analysing the geographic distribution of Azure data centres globally
Why wrong: Data centre geography is infrastructure planning — spatial analysis processes video to understand human movement in physical spaces.
- B
Analysing video to understand people's movements and interactions within physical spaces
Spatial analysis uses video AI to count people, detect zone entry, measure density, and analyse movement patterns in real-world environments.
- C
Mapping pixels in an image to three-dimensional coordinates
Why wrong: 3D reconstruction from images is computer vision geometry — spatial analysis focuses on human behaviour patterns in video streams.
- D
Categorising images by their physical dimensions and file size
Why wrong: Image metadata is file properties — spatial analysis is an AI-powered video analytics capability.
AI-900 Practice Question: Describe features of computer vision workloads on Azure
This AI-900 practice question tests your understanding of describe features of computer vision workloads on azure. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
What is 'spatial analysis' in Azure AI Vision?
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
Analysing video to understand people's movements and interactions within physical spaces
Spatial analysis in Azure AI Vision uses video analytics to detect and track people in a physical space, analyzing their movements, positions, and interactions over time. It leverages computer vision models to understand spatial relationships and patterns, such as how people move through a store or queue at a counter.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Analysing the geographic distribution of Azure data centres globally
Why it's wrong here
Data centre geography is infrastructure planning — spatial analysis processes video to understand human movement in physical spaces.
- ✓
Analysing video to understand people's movements and interactions within physical spaces
Why this is correct
Spatial analysis uses video AI to count people, detect zone entry, measure density, and analyse movement patterns in real-world environments.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Mapping pixels in an image to three-dimensional coordinates
Why it's wrong here
3D reconstruction from images is computer vision geometry — spatial analysis focuses on human behaviour patterns in video streams.
- ✗
Categorising images by their physical dimensions and file size
Why it's wrong here
Image metadata is file properties — spatial analysis is an AI-powered video analytics capability.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates confuse 'spatial' with geographic or 3D mapping concepts, when in Azure AI Vision it specifically refers to analyzing people's movements and interactions within a physical space from video feeds.
Detailed technical explanation
How to think about this question
Under the hood, spatial analysis uses the Video Indexer and custom vision models to process video frames, applying person detection, tracking, and zone-based logic to generate insights like dwell time, path heatmaps, and occupancy counts. A real-world scenario is a retailer using spatial analysis to optimize store layout by analyzing customer traffic patterns and identifying bottlenecks at checkout areas.
KKey Concepts to Remember
- Read the scenario before looking for a memorised answer.
- Find the constraint that changes the correct option.
- Eliminate answers that are true in general but not in this case.
TExam Day Tips
- Watch for words such as best, first, most likely and least administrative effort.
- Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
An e-commerce site experiences heavy traffic on Black Friday and near-zero traffic during off-peak weeks. Rather than provisioning permanent large VMs, the team uses auto-scaling groups that add capacity automatically under load and reduce it overnight. Questions like this test whether you understand elasticity, availability zones, and cloud compute scaling patterns.
What to study next
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FAQ
Questions learners often ask
What does this AI-900 question test?
Describe features of computer vision workloads on Azure — This question tests Describe features of computer vision workloads on Azure — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Analysing video to understand people's movements and interactions within physical spaces — Spatial analysis in Azure AI Vision uses video analytics to detect and track people in a physical space, analyzing their movements, positions, and interactions over time. It leverages computer vision models to understand spatial relationships and patterns, such as how people move through a store or queue at a counter.
What should I do if I get this AI-900 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Last reviewed: Jun 11, 2026
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