- A
Use Azure OpenAI On Your Data to connect to a product database so the model retrieves and references only the provided specifications.
Azure OpenAI On Your Data grounds the model on your data, making it more likely to generate responses based solely on the provided facts, thus reducing hallucinations.
- B
Increase the frequency penalty to discourage the model from repeating common phrases.
Why wrong: Frequency penalty affects repetition of tokens, not the factual accuracy or hallucination of the content.
- C
Decrease the temperature to 0 so the model always picks the most likely next token, making it more predictable.
Why wrong: While low temperature reduces randomness, the model can still generate hallucinated content because it is not constrained to the provided data.
- D
Enable content filtering to block any outputs that contain harmful or biased language.
Why wrong: Content filtering is for safety (e.g., hate speech, violence) and does not address factual accuracy or anchor the model to specific data.
Quick Answer
The correct approach is to use Azure OpenAI On Your Data, which connects the model to a specific product database so it retrieves and references only the provided specifications. This feature grounds the model’s responses in your own data, effectively preventing hallucinations by ensuring the model cannot invent external or incorrect details—it simply cannot generate information outside the connected source. On the Microsoft Azure AI-900 exam, this scenario tests your understanding of how to control model behavior for factual accuracy, often appearing as a question about reducing hallucinations in enterprise applications. A common trap is choosing prompt engineering alone, but that only guides the model without enforcing a strict data boundary. Remember the memory tip: “On Your Data” means “on your source only”—if the answer isn’t in your data, the model won’t make it up.
AI-900 Practice Question: Describe features of generative AI workloads on Azure
This AI-900 practice question tests your understanding of describe features of generative ai workloads on azure. 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.
A developer is using Azure OpenAI Service to generate product descriptions from technical specifications. The generated descriptions sometimes include plausible-sounding but incorrect details (hallucinations). The developer wants to ensure the model's responses are strictly based on the provided product data and does not add any external or invented information. Which approach should the developer use?
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 OpenAI On Your Data to connect to a product database so the model retrieves and references only the provided specifications.
Option A is correct because Azure OpenAI On Your Data allows the developer to ground the model's responses in a specific data source, such as a product database. This ensures the model retrieves and references only the provided specifications, preventing the generation of external or invented information (hallucinations). By using this feature, the model's outputs are strictly based on the connected data, aligning with the requirement for factual accuracy.
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 OpenAI On Your Data to connect to a product database so the model retrieves and references only the provided specifications.
Why this is correct
Azure OpenAI On Your Data grounds the model on your data, making it more likely to generate responses based solely on the provided facts, thus reducing hallucinations.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Increase the frequency penalty to discourage the model from repeating common phrases.
Why it's wrong here
Frequency penalty affects repetition of tokens, not the factual accuracy or hallucination of the content.
- ✗
Decrease the temperature to 0 so the model always picks the most likely next token, making it more predictable.
Why it's wrong here
While low temperature reduces randomness, the model can still generate hallucinated content because it is not constrained to the provided data.
- ✗
Enable content filtering to block any outputs that contain harmful or biased language.
Why it's wrong here
Content filtering is for safety (e.g., hate speech, violence) and does not address factual accuracy or anchor the model to specific data.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often confuse hyperparameter tuning (temperature, frequency penalty) or content filtering with data grounding, mistakenly believing these can prevent hallucinations when they only control output style or safety, not factual accuracy.
Detailed technical explanation
How to think about this question
Under the hood, Azure OpenAI On Your Data uses a retrieval-augmented generation (RAG) pattern, where the model's prompt is augmented with relevant chunks from the connected data source (e.g., Azure Cognitive Search index). This grounds the model's responses in the retrieved content, significantly reducing hallucinations by constraining the model to reference only the provided data. In a real-world scenario, a developer could connect to a Cosmos DB or SQL database containing product specs, and the model would generate descriptions by retrieving and synthesizing only those records, ignoring its internal knowledge.
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
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FAQ
Questions learners often ask
What does this AI-900 question test?
Describe features of generative AI workloads on Azure — This question tests Describe features of generative AI workloads on Azure — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Use Azure OpenAI On Your Data to connect to a product database so the model retrieves and references only the provided specifications. — Option A is correct because Azure OpenAI On Your Data allows the developer to ground the model's responses in a specific data source, such as a product database. This ensures the model retrieves and references only the provided specifications, preventing the generation of external or invented information (hallucinations). By using this feature, the model's outputs are strictly based on the connected data, aligning with the requirement for factual accuracy.
What should I do if I get this AI-900 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
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-900 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-900 exam.
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