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AI-102 Practice Question: Implement knowledge mining and information extraction solutions
Which TWO actions should you take to optimize the performance of an Azure AI Search solution that indexes large volumes of data?
⚠ Common exam trap
Test-takers frequently confuse replicas (which scale query performance) with partitions (which scale indexing throughput), leading candidates to incorrectly select option C as a way to improve indexing speed.
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
✓
Use the appropriate search tier (S1, S2, etc.) based on document size
Choosing the appropriate search tier (S1, S2, etc.) ensures that the service has sufficient resources (CPU, memory, disk I/O) to handle the indexing load and document size. Higher tiers provide better indexing throughput and storage capacity, which is critical for large volumes of data. Using an undersized tier can lead to throttling, timeouts, or failed indexing operations.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Use the appropriate search tier (S1, S2, etc.) based on document size
Why this is correct
Higher tiers have better indexing capacity.
- ✗
Use the free tier for production workloads
Why it's wrong here
Free tier has limited capacity.
- ✗
Increase the replica count for better indexing throughput
Why it's wrong here
Replicas improve query throughput, not indexing.
- ✓
Batch documents in groups of up to 1000 per index operation
Why this is correct
Batching reduces overhead.
- ✗
Disable scoring profiles to speed up indexing
Why it's wrong here
Scoring profiles don't impact indexing speed.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This AI-102 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-102 exam.