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NEW QUESTION # 96
Drag and Drop Question
You are designing end-to-end test scenarios for a business solution that uses Microsoft Dynamics
365 Sales and Dynamics 365 Finance.
You need to ensure that the business solution meets the following test requirements:
- Properly exchanges data between the Dynamics 365 apps
- Aligns with defined user workflows and business processes
Which type of testing should you use for each requirement? To answer, drag the appropriate testing types to the correct requirements. Each testing type may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
NEW QUESTION # 97
Your customer needs their custom AI agent to interact seamlessly and securely with multiple internal enterprise systems, including their ERP, CRM, and various legacy order processing APIs.
They are looking for a standardized, future-proof method for this integration that minimizes the need for developing and maintaining bespoke, fragile custom connectors for every single endpoint.
Based on Microsoft's recommended guidance for agent interoperability, which integration approach should you implement to achieve this standardized and robust cross-system communication?
Answer: C
Explanation:
Implement the Model Context Protocol (MCP) by exposing the backend REST APIs as MCP servers is correct because the Model Context Protocol (MCP) is Microsoft's strategic initiative designed to provide a standardized, universal protocol for AI agents to communicate with tools, services, and other agents. By exposing existing REST APIs as MCP servers, the customer can achieve standardized, robust, and future-proof interoperability for their AI agent across diverse internal systems, avoiding the pitfalls of custom, one-off connectors.
References:
https://learn.microsoft.com/en-us/azure/api-management/export-rest-mcp-server
https://learn.microsoft.com/en-us/microsoft-copilot-studio/agent-extend-action-mcp
NEW QUESTION # 98
A company has a Microsoft Power Platform environment that contains Microsoft Dataverse data.
You create a Microsoft Copilot Studio agent named Agent1 that processes the Dataverse data.
You discover that Agent1 fails to return relevant or accurate results. You need to improve the quality and reliability of data grounding. What should you do?
Answer: D
Explanation:
If a Copilot Studio agent that uses Dataverse is returning poor or irrelevant results, the most likely issue is weak or inconsistent grounding data.
The best corrective action is C. Verify and cleanse the Dataverse data.
Why C is correct:
Grounded AI quality depends heavily on source data quality
Incomplete, inconsistent, duplicated, outdated, or badly structured Dataverse records will lead to poor answers Cleansing and validating the data improves both relevance and reliability without requiring unnecessary model changes
NEW QUESTION # 99
You are designing a Microsoft Copilot Studio agent that uses a custom Microsoft Foundry model to generate responses.
You need to ensure that the agent can securely connect to and invoke the custom model during user interactions.
What should you include in the design?
Answer: B
Explanation:
To create a connection to Microsoft Foundry within a Microsoft Copilot Studio agent and securely invoke a custom model, follow these steps:
1. Connect via the "External Agent" Method
This method allows your Copilot Studio agent to orchestrate and call a specific Microsoft Foundry agent directly.
2. Connect via "Bring Your Own Model" (BYOM)
If you want to use a specific model from the Foundry model catalog for individual prompt actions.
3. Security and Governance
Connecting to Microsoft Foundry ensures enterprise-grade security through:
Entra ID Integration: Agents are assigned a unique Microsoft Entra Agent ID, allowing IT teams to enforce Conditional Access and Identity Governance.
Unified Management: Both your Copilot Studio and Foundry agents can be managed centrally in the Microsoft Entra admin center.
Reference:
https://techcommunity.microsoft.com/blog/azure-ai-foundry-blog/building-secure-governable-ai- agents-with-microsoft-foundry/4472736
NEW QUESTION # 100
You use Microsoft Copilot Studio analytics to analyze the performance of a deployed Copilot Studio agent.
You need to identify which performance metrics to use to measure the following:
* The percentage of engaged sessions that are escalated to a live customer service representative
* The number of agent queries that cause a knowledge source error
What should you identify for each requirement? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
In Microsoft Copilot Studio analytics , each metric is designed to measure a different aspect of agent performance.
For the first requirement, the metric that tracks the percentage of engaged sessions escalated to a live customer service representative is Escalation rate . This directly measures how often conversations are handed off from the agent to a human.
For the second requirement, the metric th at helps identify queries causing a knowledge source error is Answer quality . This area evaluates how well the agent responds and includes issues related to grounded answers, failed responses, and knowledge-source-related problems.
Why the other options are not correct:
* Customer Satisfaction (CSAT) score measures user satisfaction, not escalation percentage or knowledge source errors.
* Engagement rate measures whether users actively interact with the agent, not whether sessions are escalated or whether a kno wledge source failed.
NEW QUESTION # 101
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