- A
Azure AI Language for translation and sentiment, and Azure AI Computer Vision for attribute extraction.
Why wrong: Language does not translate; Computer Vision is for images, not text attributes.
- B
Azure AI Speech for translation, Azure AI Language for sentiment, and Azure AI Search for storage.
Why wrong: Speech is for audio, not text translation.
- C
Azure AI Translator for translation, Azure AI QnA Maker for attribute extraction, and Azure SQL Database for storage.
Why wrong: QnA Maker is not for attribute extraction.
- D
Azure AI Translator for translation, Azure AI Language for sentiment and entity extraction, and Azure AI Search to index the results.
Translator provides real-time translation, Language provides sentiment and entity extraction, and Search stores results for analytics.
Quick Answer
The correct combination is Azure AI Translator, Azure AI Language, and Azure AI Search. Azure AI Translator handles real-time multilingual translation across 12 languages, while Azure AI Language performs both sentiment analysis and entity extraction to identify key product attributes like color and size from unstructured review text. Azure AI Search then indexes these processed results, enabling low-latency analytics and cost efficiency by avoiding unnecessary services like Speech or Computer Vision. On the AI-102 exam, this scenario tests your ability to match specific text analytics tasks to the right services—a common trap is overcomplicating the solution with Azure AI Document Intelligence or Cognitive Search alone, which lack native sentiment or entity extraction. Remember the memory tip: “Translate, Analyze, Index”—each service owns one core function, and combining them minimizes latency by keeping processing in the text domain without redundant overhead.
AI-102 Plan and manage an Azure AI solution Practice Question
This AI-102 practice question tests your understanding of plan and manage an azure ai solution. 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 designing an Azure AI solution for a global e-commerce company. The solution must: (1) Translate product descriptions into 12 languages in real-time. (2) Detect sentiment in customer reviews for each language. (3) Extract key product attributes (e.g., color, size) from unstructured review text. (4) Store results in a centralized database for analytics. The solution must minimize latency and cost. You plan to use Azure AI services. Which combination of services should you use?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue:
"minimum / minimize"Why it matters: Asks for the least resource use — fewest addresses, smallest subnet, lowest overhead. Eliminate over-provisioned options even if they would technically work.
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
Azure AI Translator for translation, Azure AI Language for sentiment and entity extraction, and Azure AI Search to index the results.
Option D is correct because Azure AI Translator provides real-time translation into 12 languages, Azure AI Language handles both sentiment analysis and entity extraction (for attributes like color and size) from unstructured text, and Azure AI Search indexes the results for low-latency analytics. This combination minimizes latency by using dedicated services for each task and avoids unnecessary overhead from services like Speech or Computer Vision that are not required for text-only processing.
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.
- ✗
Azure AI Language for translation and sentiment, and Azure AI Computer Vision for attribute extraction.
Why it's wrong here
Language does not translate; Computer Vision is for images, not text attributes.
- ✗
Azure AI Speech for translation, Azure AI Language for sentiment, and Azure AI Search for storage.
Why it's wrong here
Speech is for audio, not text translation.
- ✗
Azure AI Translator for translation, Azure AI QnA Maker for attribute extraction, and Azure SQL Database for storage.
Why it's wrong here
QnA Maker is not for attribute extraction.
- ✓
Azure AI Translator for translation, Azure AI Language for sentiment and entity extraction, and Azure AI Search to index the results.
Why this is correct
Translator provides real-time translation, Language provides sentiment and entity extraction, and Search stores results for analytics.
Clue confirmation
The clue word "minimum / minimize" 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 may confuse Azure AI Language's entity extraction with Azure AI Computer Vision or QnA Maker, assuming attribute extraction requires visual analysis or Q&A logic, when in fact it is a text-based NLP task handled by the Language service.
Detailed technical explanation
How to think about this question
Azure AI Translator uses a neural machine translation (NMT) engine that supports dynamic dictionary and custom terminology for domain-specific terms, ensuring accurate real-time translation. Azure AI Language's entity extraction leverages a pre-trained model that can identify custom categories like product attributes via the 'Custom Entity Recognition' feature, which can be fine-tuned with labeled data. Azure AI Search integrates with these services via indexers and cognitive skills, enabling enrichment pipelines that automatically extract and store insights with sub-second query latency.
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 startup's cloud architect reviews their monthly bill and notices costs are higher than expected for a long-running batch job. Switching from on-demand instances to Reserved Instances — or using Spot/Preemptible VMs — can reduce compute costs by up to 72 %. Questions like this test whether you understand the tradeoffs between commitment, flexibility, and cost across cloud pricing models.
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?
Plan and manage an Azure AI solution — This question tests Plan and manage an Azure AI solution — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Azure AI Translator for translation, Azure AI Language for sentiment and entity extraction, and Azure AI Search to index the results. — Option D is correct because Azure AI Translator provides real-time translation into 12 languages, Azure AI Language handles both sentiment analysis and entity extraction (for attributes like color and size) from unstructured text, and Azure AI Search indexes the results for low-latency analytics. This combination minimizes latency by using dedicated services for each task and avoids unnecessary overhead from services like Speech or Computer Vision that are not required for text-only processing.
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: "minimum / minimize". Asks for the least resource use — fewest addresses, smallest subnet, lowest overhead. Eliminate over-provisioned options even if they would technically work.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
About these practice questions
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Last reviewed: Jun 24, 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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