- A
Set continueOnError to false to ensure that if the skill fails for one document, the entire indexer run stops.
Why wrong: Setting continueOnError to false would cause the entire run to fail; it's better to set it to true to skip failures for individual documents.
- B
Set the inputs of the skill to include the 'text' field from the enriched document and the 'product' field from a previous skill.
Inputs define the data passed to the skill; they should reference fields from the enrichment pipeline.
- C
Set the uri of the skill to the HTTP endpoint of the Azure Function, including the function key.
Custom skills must point to the function's endpoint; Azure Functions are typically accessed via an HTTP URL with a code or key.
- D
Set the context property to '/document/pages/*' to process each page of the email individually.
Why wrong: Emails are not paginated; setting context to '/document' is appropriate to process the entire document.
- E
Set the batchSize of the custom skill definition to 10 to allow parallel processing of multiple documents.
A higher batchSize allows the indexer to send multiple documents per skill invocation, improving throughput.
Quick Answer
The correct answer is to set the batchSize of the custom skill definition to 10, configure the skill’s inputs to include both the email body text and the product field from a prior skill, and implement error handling within the Azure Function to return a failure status for individual records. This configuration is correct because Azure Cognitive Search processes documents in parallel based on the batchSize parameter—setting it to 10 allows the indexer to send up to ten documents concurrently to your custom skill, maximizing throughput. Additionally, the custom skill must receive the email body for sentiment analysis and the product field (extracted by a preceding skill like entity recognition) as distinct inputs to produce both a sentiment score and the primary product name. On the AI-102 exam, this tests your understanding of custom skill pipelines and the indexer’s parallel processing model; a common trap is forgetting that inputs must map to prior skill outputs, not raw fields. Remember the mnemonic “Batch, Inputs, Handle” to recall the three required configurations: batchSize, proper input mapping, and graceful error handling.
AI-102 Practice Question: Implement knowledge mining and document intelligence solutions
This AI-102 practice question tests your understanding of implement knowledge mining and document intelligence solutions. This is a configuration task: choose the command set that satisfies every stated requirement. Small differences — like 'secret' vs 'password' or 'transport input ssh' vs 'all' — change whether the answer is correct. 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.
A company uses Azure Cognitive Search to index customer support emails. They need to implement a custom skill that extracts the sentiment of the email body and also identifies the primary product mentioned. The custom skill is a Python function deployed as an Azure Function. They want to ensure the skill can process multiple documents concurrently and handle errors gracefully. Which THREE configurations should they apply?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue:
"primary"Why it matters: Asks for the main purpose or function, not a secondary benefit. Eliminate answers that describe side-effects or partial functions.
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
Set the inputs of the skill to include the 'text' field from the enriched document and the 'product' field from a previous skill.
Option B is correct because the custom skill must receive the email body text for sentiment analysis and the product field from a prior skill (e.g., a key phrase extraction or entity recognition skill) to identify the primary product. This ensures the Azure Function has all required inputs to produce the desired outputs (sentiment score and product name).
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.
- ✗
Set continueOnError to false to ensure that if the skill fails for one document, the entire indexer run stops.
Why it's wrong here
Setting continueOnError to false would cause the entire run to fail; it's better to set it to true to skip failures for individual documents.
- ✓
Set the inputs of the skill to include the 'text' field from the enriched document and the 'product' field from a previous skill.
Why this is correct
Inputs define the data passed to the skill; they should reference fields from the enrichment pipeline.
Clue confirmation
The clue word "primary" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
- ✓
Set the uri of the skill to the HTTP endpoint of the Azure Function, including the function key.
Why this is correct
Custom skills must point to the function's endpoint; Azure Functions are typically accessed via an HTTP URL with a code or key.
Clue confirmation
The clue word "primary" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Set the context property to '/document/pages/*' to process each page of the email individually.
Why it's wrong here
Emails are not paginated; setting context to '/document' is appropriate to process the entire document.
- ✓
Set the batchSize of the custom skill definition to 10 to allow parallel processing of multiple documents.
Why this is correct
A higher batchSize allows the indexer to send multiple documents per skill invocation, improving throughput.
Clue confirmation
The clue word "primary" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often confuse the 'context' property with the 'inputs' property, incorrectly assuming that setting context to '/document/pages/*' is necessary for page-level processing, when in fact the context should match the granularity at which the skill should operate—here, the entire document for overall sentiment.
Detailed technical explanation
How to think about this question
The batchSize property (Option E) controls how many documents are sent to the custom skill in a single HTTP request, enabling parallel processing; the Azure Function must be designed to handle an array of records. The URI (Option C) must include the function key for authentication, typically as a query parameter (e.g., ?code=...), and the skill definition must use the 'uri' property to point to the Azure Function's HTTP trigger endpoint. Under the hood, Cognitive Search sends a JSON payload with an array of 'values', each containing the input fields, and expects a response with corresponding 'values' containing outputs or errors.
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.
TExam Day Tips
- 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.
What to study next
Got this wrong? Here's your next step.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
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FAQ
Questions learners often ask
What does this AI-102 question test?
Implement knowledge mining and document intelligence solutions — This question tests Implement knowledge mining and document intelligence solutions — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Set the inputs of the skill to include the 'text' field from the enriched document and the 'product' field from a previous skill. — Option B is correct because the custom skill must receive the email body text for sentiment analysis and the product field from a prior skill (e.g., a key phrase extraction or entity recognition skill) to identify the primary product. This ensures the Azure Function has all required inputs to produce the desired outputs (sentiment score and product name).
What should I do if I get this AI-102 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Are there clue words in this question I should notice?
Yes — watch for: "primary". Asks for the main purpose or function, not a secondary benefit. Eliminate answers that describe side-effects or partial functions.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Last reviewed: Jun 11, 2026
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.
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