Implement knowledge mining and information extraction solutions →mediumMultiple ChoiceObjective-mapped
AI-102 Practice Question: Implement knowledge mining and information extraction solutions
You are building a knowledge mining solution for a financial services company that needs to extract key financial terms (e.g., revenue, EBITDA, net income) from annual reports in PDF format. The solution must use a custom skill that runs a Python script to perform the extraction. The Python script is deployed as an Azure Function. You have added the custom skill to the skillset and tested it with a small set of documents. However, when processing the full dataset, the custom skill fails with time-out errors. The Azure Function has a default timeout of 230 seconds. What should you do to resolve the issue without changing the extraction logic?
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
✓
Change the Azure Function to a Premium plan and increase the function timeout.
The custom skill fails with time-out errors because the Azure Function's default timeout of 230 seconds is too short for processing large documents. Option D is correct because upgrading to a Premium plan allows you to increase the function timeout (up to 30 minutes with Premium plan, or unlimited with Dedicated plan). Option A is wrong because the indexer's batch size controls how many documents are processed simultaneously, but the timeout is per document (or per skill execution), so smaller batches won't solve the per-document timeout issue. Option B is wrong because Document Intelligence custom extraction models are pre-built for common forms and are not suitable for custom Python extraction logic. Option C is wrong because splitting the skillset does not change the execution time of the individual skill; the same timeout per invocation would still apply.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Configure the indexer to process documents in smaller batches.
Why it's wrong here
Batching controls how many documents are processed concurrently, not the timeout per document.
- ✗
Replace the custom skill with a Document Intelligence custom extraction model.
Why it's wrong here
Document Intelligence would require retraining and is not a direct substitute for Python logic.
- ✗
Split the skillset into multiple skillsets and run them sequentially.
Why it's wrong here
This would not reduce the per-document execution time for each call.
- ✓
Change the Azure Function to a Premium plan and increase the function timeout.
Why this is correct
Premium plan allows longer timeouts, giving the script more time to execute.
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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.