AI-200 Data Management Services And Vector Search Practice Question
When configuring vector search in Azure Cosmos DB for NoSQL, which TWO properties must be defined within the container's vector embedding policy? Choose two.
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
✓
Path (the JSON property containing the vector array)
In Azure Cosmos DB for NoSQL, the vector embedding policy requires defining paths (properties containing vectors) and embedding details such as datatype, dimensions, and distance function.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Container partition key definition
Why it's wrong here
The partition key is a container-level configuration, not part of the vector embedding policy.
- ✗
BM25 k1 and b tuning parameters
Why it's wrong here
BM25 parameters are for full-text search, not vector embedding policies.
- ✗
Replication lag threshold
Why it's wrong here
Replication lag is a consistency setting, not a vector embedding policy property.
- ✓
Path (the JSON property containing the vector array)
Why this is correct
The path specifies which property in the JSON document holds the embedding array.
- ✓
DataType (e.g., float32) and Dimensions (e.g., 1536)
Why this is correct
DataType and Dimensions define the structural characteristics of the stored vectors.
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JA
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
This AI-200 practice question is part of Courseiva's free Microsoft certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the AI-200 exam.