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NEW QUESTION # 91
Hotspot Question
Select the answer that correctly completes the sentence.
Answer:
Explanation:
Explanation:
Box: Batch API
An organization that runs continuous, large-scale workloads with Azure OpenAI models should choose the _______ pricing model.
An organization that runs continuous, large-scale, non-time-sensitive workloads with Azure OpenAI models should choose the Batch API pricing model.
This approach provides significant cost savings and operational advantages for high-volume, asynchronous tasks.
For continuous, non-urgent workloads, the Batch API provides the best balance of cost- effectiveness and throughput, often allowing organizations to cut their AI inference costs in half while maximizing scalability.
Reference:
https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/batch?view=foundry-classic
NEW QUESTION # 92
You have a historical dataset that contains 1,000 records.
You need an AI solution that can analyze the data to identify patterns and predict future outcomes.
What should you include in the solution?
Answer: C
Explanation:
The primary Microsoft AI solution designed to analyze large, historical datasets (thousands of records), identify complex patterns, and predict future outcomes is Azure Machine Learning, specifically utilizing Automated Machine Learning (AutoML).
Reference:
https://vslive.com/blogs/mshq-news-and-events/2025/04/azure-ml.aspx
NEW QUESTION # 93
Drag and Drop Question
Match the business scenario to the appropriate AI solution design approach.
To answer, drag the AI solution from the column on the left to its business scenario on the right.
Each solution may be used once, more than once, or not at all.
NOTE: Each correct match is worth one point.
Answer:
Explanation:
Explanation:
Box 1: Build with Microsoft Copilot Studio
The marketing department at your company wants AI to summarize emails and create presentations.
Building an AI solution to summarize emails and create presentations using Microsoft Copilot Studio involves creating custom AI agents that leverage your company's Microsoft 365 data (emails, documents) to automate these workflows. Copilot Studio allows you to create, test, and publish conversational agents that can be integrated into Microsoft Teams or directly into Office apps.
Box 2: Use Microsoft 365 Copilot
The HR department at your company wants a conversational agent for policy questions and leave request.
A company can use Microsoft 365 Copilot to create a conversational agent for policy questions and leave requests, primarily by leveraging Copilot Studio to customize agents with specific organizational data. These agents can function within Microsoft Teams, providing a self-service,
24/7 interface for employees.
Box 3: Build with Azure Machine Learning
The manufacturing department at your company wants AI to predict maintenance schedules.
Azure Machine Learning (Azure ML) is a powerful, cloud-based platform that helps companies shift from reactive or scheduled maintenance to predictive maintenance, which optimizes maintenance schedules based on actual equipment health.
By leveraging IoT sensors, historical data, and AI, Azure ML enables organizations to forecast equipment failures before they occur, reducing downtime and maintenance costs.
Box 4: Extend with Microsoft 365 Copilot connectors
The finance department at your company wants AI-powered access to enterprise resource planning (ERP) data by using familiar productivity tools You can extend Microsoft 365 Copilot with connectors to enable AI-powered access to enterprise resource planning (ERP) data directly within productivity tools like Outlook, Teams, and Excel.
This integration allows users to query, summarize, and act on data from systems such as SAP, Oracle, and Dynamics 365 without switching between applications.
Reference:
https://techcommunity.microsoft.com/blog/azurecommunicationservicesblog/build-your-ai-email- agent-with-microsoft-copilot-studio/4448724
https://adoption.microsoft.com/en-us/scenario-library/human-resources/leave-of-absence- compliance-agent
https://learn.microsoft.com/en-us/azure/documentdb/solutions-iot
https://www.mtlc.co/how-to-unlock-the-power-of-microsoft-365-copilot-connectors
NEW QUESTION # 94
Your company stores thousands of reports and documents across multiple systems.
You recommend using Azure AI Search as part of a new generative AI solution to improve information discovery.
What is a key benefit of using Azure AI Search in this scenario?
Answer: C
Explanation:
In an environment with tens of thousands of reports and documents across multiple systems, Azure AI Search (formerly Cognitive Search) significantly improves information discovery through several core mechanisms:
*-> Natural Language & Semantic Search: Unlike traditional keyword search, it understands the intent and context behind queries. Users can ask conversational questions (e.g., "Find all contracts mentioning GDPR compliance in 2023") and receive relevant results even without exact keyword matches.
*-> Unified Multi-System Ingestion: It uses indexers to automatically pull and unify data from diverse sources such as SharePoint, Azure Blob Storage, SQL databases, and Cosmos DB into a single searchable index.
AI-Powered Content Enrichment: During indexing, it can apply cognitive skills to extract information from unstructured data. This includes:
- Optical Character Recognition (OCR) to make scanned reports searchable.
- Entity Recognition to identify and tag people, locations, and organizations.
- Key Phrase Extraction and language detection to enhance metadata.
-Hybrid Retrieval: It combines vector search (for semantic meaning) with full-text search (for specific terms like product codes or names), merging them via Reciprocal Rank Fusion (RRF) to ensure high precision and recall.
Semantic Ranking: An advanced L2 ranking layer uses deep learning models from Bing to re- order the top search results, ensuring the most contextually relevant answers appear first.
This setup is commonly used as the retrieval foundation for Retrieval-Augmented Generation (RAG), where search results are fed into Large Language Models (LLMs) like GPT-4 to provide grounded, human-like answers based on your enterprise data.
Reference:
https://azure.microsoft.com/en-us/products/ai-services/ai-search
NEW QUESTION # 95
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
* Microsoft 365 Copilot helps users create and analyze content in Microsoft 365 apps. Answer: Yes
* Microsoft Copilot Studio can only be used to customize Microsoft 365 Copilot. Answer: No
* Microsoft Security Copilot uses AI to assign sensitivity labels to documents. Answer: No
* Yes - Microsoft 365 Copilot is built into Microsoft 365 apps (such as Word, Excel, PowerPoint, Outlook, and Teams) to help users draft, summarize, rewrite, and analyze work content. This includes creating documents and presentations, summarizing emails and meetings, and analyzing information in productivity workflows. That is its primary value proposition, so the statement is true.
* No - Copilot Studio is not limited to customizing Microsoft 365 Copilot. It is used to build and manage agents (conversational experiences) and extend Copilot experiences by connecting to data and actions, creating custom topics/behaviors, and integrating business processes. While it can be used to extend Microsoft 365 Copilot (for example, via declarative agents and other extensibility paths), it is broader than "only customizing Microsoft 365 Copilot," so the statement is false.
* No - Assigning sensitivity labels to documents is primarily a Microsoft Purview Information Protection capability (manual labeling, default labeling, auto-labeling) rather than a core function of Microsoft Security Copilot. Security Copilot is focused on security operations (incident investigation, threat hunting, response guidance). Although AI can support security workflows, the specific act of assigning sensitivity labels to documents is not what Security Copilot is designed to do by default, making the statement false.
NEW QUESTION # 96
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