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NEW QUESTION # 50
- For each of the following statements, select Yes if the statement is true. Otherwise, select No. NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Answer Area
* To use Microsoft 365 Copilot Chat, you must have a Microsoft 365 Copilot license. Answer: No
* Microsoft 365 Copilot Chat provides context-aware assistance in Microsoft 365 apps. Answer: Yes
* Microsoft 365 Copilot Chat can only access information in open files and read emails. Answer: No
* No - Microsoft documents and pricing guidance indicate that Copilot Chat is available for eligible Microsoft Entra ID users with a qualifying Microsoft 365 subscription , and that capabilities can vary depending on whether users also have the Microsoft 365 Copilot add-on . In other words, Copilot Chat isn't universally "Copilot-license required" in all cases; the add-on impacts which premium work features are enabled, but the baseline chat experience can be available without assigning the add-on to every user.
* Yes - Microsoft describes Copilot Chat as a side-by-side experience in select Microsoft 365 apps (for example Word, Excel, PowerPoint, OneNote, Outlook) that is aware of the user's open content , enabling context-aware help such as summarizing, drafting, and Q & A based on what the user is working on.
* No - The word only makes this statement inaccurate. Copilot Chat can be grounded in more than just open files and emails (for example, it can also be grounded in the web, and-depending on licensing and configuration-can use agents/connectors for broader scoped tasks). So limiting it strictly to "open files and read emails" is too restrictive compared to how Microsoft positions the feature set.
NEW QUESTION # 51
Your company uses a non-reasoning generative AI model to create textual content. You discover that the model's responses are inconsistent and do NOT meet expectations. You need to improve the prompts. What should you do? More than one answer choice may achieve the goal. Select the BEST answer.
Answer: B,C
Explanation:
When a non-reasoning generative AI model produces inconsistent outputs, the most reliable improvement is to make the prompt more specific, constrained, and demonstrative of what "good" looks like.
A is correct because adding high-quality examples is a form of few-shot prompting. Examples act like
"training wheels" at inference time: they show the model the desired structure, tone, level of detail, formatting rules, and boundaries. This reduces ambiguity and variance, especially for tasks like marketing copy, summaries, policy text, or customer replies. The more your examples resemble real target outputs (including edge cases), the more consistent the model's completions become.
B is correct because adding context, relevant source material, and explicit expectations narrows the model's degrees of freedom. Including the intended audience, purpose, constraints (length, voice, banned claims), and trusted reference content (approved facts, product specs, policy excerpts) helps the model stay aligned and reduces hallucinations and off-brand language. This is also where you specify acceptance criteria such as
"must include 3 bullet points," "use UK English," or "cite only provided text." C is not best: technical jargon can confuse or bias output if it's not aligned to the task; clarity beats jargon. D is not best: a single concise requirement is usually under-specified and often increases variability.
NEW QUESTION # 52
You need to recommend a service that supports indexing information and knowledge mining by extracting insights from documents. What should you recommend?
Answer: A
Explanation:
The requirement has two key phrases: indexing information and knowledge mining by extracting insights from documents . The Microsoft service purpose-built for this is Azure AI Search (formerly Azure Cognitive Search), which provides a search index over your content and supports "AI enrichment" workflows to extract and structure insights from documents during indexing.
Azure AI Search can ingest content from common enterprise sources (files, blobs, databases), build searchable indexes, and enrich the indexed content using built-in skills or integrated AI capabilities-such as entity recognition, key phrase extraction, language detection, and OCR (depending on the pipeline). This is exactly what "knowledge mining" refers to: turning large volumes of unstructured documents into structured, searchable knowledge that applications and users can query.
The other choices are partial fits: Azure Vision focuses on image/video analysis, not general document indexing. Azure Document Intelligence is excellent for extracting fields/tables from forms and documents, but on its own it does not provide the full indexing/search and knowledge mining layer across a corpus.
Microsoft Foundry is an overarching platform for building AI apps/agents; it can incorporate search, but the specific service that directly delivers indexing + knowledge mining is Azure AI Search .
NEW QUESTION # 53
Your company plans to use generative AI to help summarize and analyze internal business documents.
You need to recommend a solution to prevent generative AI from accessing confidential or classified information.
What should you include in the recommendation?
Answer: D
Explanation:
Data governance is essential to prevent generative AI (GenAI) from accessing confidential or classified information, as it provides the necessary framework, policies, and controls to manage data security throughout the AI lifecycle. Effective governance involves a combination of data classification, strict access controls, and active monitoring to ensure only authorized, non- sensitive data is used.
Reference:
https://dacodes.com/blog/data-governance-best-practices-for-generative-ai
NEW QUESTION # 54
Hotspot Question
Select the answer that correctly completes the sentence.
Answer:
Explanation:
NEW QUESTION # 55
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