The answer is a data source that points to the document store, a skillset with key phrase extraction and language detection skills, and a search index to store the enriched data. These three components form the core of an Azure AI Search skillset pipeline: the data source ingests raw documents, the skillset applies Azure AI Language’s key phrase extraction and language detection to enrich each document, and the search index stores the resulting structured, searchable content. On the Microsoft Azure AI Engineer Associate AI-102 exam, this question tests your understanding of the required building blocks for a knowledge mining solution, often tripping candidates who confuse the indexer (the orchestrator) with the index itself, or who mistakenly add custom skills as mandatory. Remember the pipeline mantra: source in, skills enrich, index out—three distinct pieces, no more. A useful memory tip is “DSI”: Data source, Skillset, Index—the three pillars you must always configure for any enrichment workflow.
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. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. 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 that uses Azure Cognitive Search and Azure AI Language. The solution must extract key phrases and detect the language of documents. Which THREE components are required?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
A search index that contains fields for the extracted data.
Options A, C, and D are correct. A skillset with key phrase extraction and language detection skills (A), a data source connecting to the documents (C), and a search index to store the enriched data (D). Option B is wrong because the indexer is required, but the index is needed too. Option E is wrong because custom skills are not required.
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.
✗
A custom skill to combine key phrases and language.
Why it's wrong here
No custom skill is needed.
✓
A search index that contains fields for the extracted data.
Why this is correct
The index stores the enriched content.
Related concept
Read the scenario before looking for a memorised answer.
✓
A skillset that includes the built-in Key Phrase Extraction and Language Detection skills.
Why this is correct
These skills are needed for extraction.
Related concept
Read the scenario before looking for a memorised answer.
✓
A data source that points to the document store.
Why this is correct
Documents need to be accessed via a data source.
Related concept
Read the scenario before looking for a memorised answer.
✗
An indexer that runs on a schedule.
Why it's wrong here
An indexer is required but not listed; this option is a schedule, not the indexer itself.
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.
What to study next
Got this wrong? Here's your next step.
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.
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: A search index that contains fields for the extracted data. — Options A, C, and D are correct. A skillset with key phrase extraction and language detection skills (A), a data source connecting to the documents (C), and a search index to store the enriched data (D). Option B is wrong because the indexer is required, but the index is needed too. Option E is wrong because custom skills are not required.
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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Question Discussion
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