- A
Use Azure AI Search with a skillset that includes OCR skill, Text Translation skill to translate, Entity Recognition skill for drugs, and Key Phrase Extraction. Index the results.
Why wrong: Translation is unnecessary; OCR may not be optimal for digital PDFs.
- B
Use Azure AI Search with a blob indexer that includes a skillset with Document Layout skill to extract text, Key Phrase Extraction skill to extract key findings, and map built-in metadata for title, authors, date. Use a custom index to store the extracted fields.
Why wrong: Missing drug/dosage extraction; no Entity Recognition skill.
- C
Use Azure AI Search with a blob indexer and a skillset that includes Document Layout skill, Entity Recognition skill to extract drug names, Key Phrase Extraction skill, and custom skill to extract title/authors/date from the first page. Create an index with fields for each required element.
Covers all requirements with appropriate skills.
- D
Use Azure AI Search with a skillset that includes OCR skill, Entity Recognition skill, Sentiment skill, and Key Phrase Extraction. Use a knowledge store to project the enriched data.
Why wrong: Sentiment is not required; OCR may not be optimal; knowledge store is overkill.
Quick Answer
The answer is to use Azure AI Search with a blob indexer and a skillset that includes the Document Layout skill, Entity Recognition skill for drugs, Key Phrase Extraction skill, and a custom skill to parse the first page for title, authors, and date. This approach is correct because the Document Layout skill is specifically designed to handle the tables and figures found in medical PDFs, while Entity Recognition targets drug mentions as a predefined category, and Key Phrase Extraction surfaces the key findings—all feeding into an index with dedicated fields for each required element. On the AI-102 exam, this scenario tests your ability to select the right combination of built-in skills versus custom logic for structured document extraction, with a common trap being to overuse OCR (which is redundant for text-based PDFs) or to forget Entity Recognition for drug detection. A useful memory tip is “Layout, Entity, Key, Custom” to recall the four skill components needed for medical document extraction.
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 a data scientist at a healthcare research organization. You have been tasked with building a knowledge mining solution to extract key information from thousands of medical journal articles stored as PDFs in an Azure Blob Storage container. The articles are in English and contain tables, figures, and structured text. Your organization uses Microsoft Purview for data governance. You need to design a solution that uses Azure AI Search and Azure AI Services to extract and index the following: article title, authors, publication date, abstract, and key findings (as key phrases). The solution must also detect any mentions of drugs and dosages. The extracted information must be indexed and searchable via a custom web application. Which approach should you take?
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 Azure AI Search with a blob indexer and a skillset that includes Document Layout skill, Entity Recognition skill to extract drug names, Key Phrase Extraction skill, and custom skill to extract title/authors/date from the first page. Create an index with fields for each required element.
Option C is correct because it uses the appropriate skills for extraction: Document Layout skill handles tables and figures, Entity Recognition extracts drugs (as entities), Key Phrase Extraction extracts key findings, and the index includes all required fields. Option A misses Entity Recognition for drugs. Option B uses Translator unnecessarily. Option D uses OCR skill but the Document Layout skill is more suitable for structured PDFs.
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.
- ✗
Use Azure AI Search with a skillset that includes OCR skill, Text Translation skill to translate, Entity Recognition skill for drugs, and Key Phrase Extraction. Index the results.
Why it's wrong here
Translation is unnecessary; OCR may not be optimal for digital PDFs.
- ✗
Use Azure AI Search with a blob indexer that includes a skillset with Document Layout skill to extract text, Key Phrase Extraction skill to extract key findings, and map built-in metadata for title, authors, date. Use a custom index to store the extracted fields.
Why it's wrong here
Missing drug/dosage extraction; no Entity Recognition skill.
- ✓
Use Azure AI Search with a blob indexer and a skillset that includes Document Layout skill, Entity Recognition skill to extract drug names, Key Phrase Extraction skill, and custom skill to extract title/authors/date from the first page. Create an index with fields for each required element.
Why this is correct
Covers all requirements with appropriate skills.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Use Azure AI Search with a skillset that includes OCR skill, Entity Recognition skill, Sentiment skill, and Key Phrase Extraction. Use a knowledge store to project the enriched data.
Why it's wrong here
Sentiment is not required; OCR may not be optimal; knowledge store is overkill.
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 media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.
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.
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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: Use Azure AI Search with a blob indexer and a skillset that includes Document Layout skill, Entity Recognition skill to extract drug names, Key Phrase Extraction skill, and custom skill to extract title/authors/date from the first page. Create an index with fields for each required element. — Option C is correct because it uses the appropriate skills for extraction: Document Layout skill handles tables and figures, Entity Recognition extracts drugs (as entities), Key Phrase Extraction extracts key findings, and the index includes all required fields. Option A misses Entity Recognition for drugs. Option B uses Translator unnecessarily. Option D uses OCR skill but the Document Layout skill is more suitable for structured PDFs.
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.
About these practice questions
Courseiva creates original exam-style practice questions with explanations and wrong-answer analysis. It does not publish real exam questions, exam dumps, or protected exam content. Learn why practice questions differ from exam dumps →
Last reviewed: Jun 20, 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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