AI-200 Data Management Services And Vector Search Practice Question
When designing an Azure AI Search solution, you need to store high-dimensional embeddings. Which field type must be used to store these vector representations correctly?
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
✓
Collection(Edm.Single)
In Azure AI Search, vector embeddings must be defined using the 'Collection(Edm.Single)' field type.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Edm.Double
Why it's wrong here
Edm.Double is for numerical values, not vector arrays.
- ✓
Collection(Edm.Single)
Why this is correct
This is the required data type for storing vector embeddings in Azure AI Search indexes.
- ✗
Edm.String
Why it's wrong here
Edm.String is for text fields and cannot be used for vector search operations.
- ✗
Collection(Edm.Int32)
Why it's wrong here
Integer collections are not compatible with vector similarity search algorithms.
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Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed August 2026 · checked against the official Microsoft exam blueprint
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