- A
Configure the indexer to process documents in smaller batches.
Why wrong: Batching controls how many documents are processed concurrently, not the timeout per document.
- B
Replace the custom skill with a Document Intelligence custom extraction model.
Why wrong: Document Intelligence would require retraining and is not a direct substitute for Python logic.
- C
Split the skillset into multiple skillsets and run them sequentially.
Why wrong: This would not reduce the per-document execution time for each call.
- D
Change the Azure Function to a Premium plan and increase the function timeout.
Premium plan allows longer timeouts, giving the script more time to execute.
Question 419 of 993
Implement knowledge mining and information extraction solutions →mediumMultiple ChoiceObjective-mapped
AI-102 Practice Question: Implement knowledge mining and information extraction solutions
This AI-102 practice question tests your understanding of implement knowledge mining and information extraction solutions. The scenario asks you to isolate a root cause — eliminate options that address a different problem before choosing. 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.
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.
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.
- ✗
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.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Many certification questions include familiar terms but test a specific constraint. Read the exact wording before choosing an answer that is generally true but wrong for this case.
Detailed technical explanation
How to think about this question
This question should be treated as a scenario, not a definition check. Identify the problem, the constraint and the best action. Then compare each option against those facts.
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.
- Use explanations to understand the rule behind the answer.
TExam Day Tips
- Underline the problem statement mentally.
- 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
A cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.
Visual reference
What to study next
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FAQ
Questions learners often ask
What does this AI-102 question test?
Implement knowledge mining and information extraction solutions — This question tests Implement knowledge mining and information extraction solutions — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: 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.
What should I do if I get this AI-102 question wrong?
Identify which AI-102 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Last reviewed: Jun 20, 2026
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