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質問 # 84
A company has Microsoft Power Platform development staging, and production environments. Each environment has its own Microsoft Dataverse tables and Azure Al Search index.
You are designing an application lifecycle management (ALM) process to deploy a Microsoft Copilot Studio agent between the environments.
The company has a Copilot Studio agent named Agent! in development. Agent1 uses the following grounding data sources:
* A Dataverse table named CustomerOrders
* An Azure Al Search index named customer-knowledge
You need to deploy Agent1 to production. The solution must ensure that the agent uses the production grounding data sources, minimizes downtime, and handles credentials and endpoints securely.
What should you include in the deployment package solution, and what should you reconfigure after the deployment? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
正解：
解説：
Explanation:
In a proper ALM deployment for Microsoft Copilot Studio across development, staging, and production, you should package the agent in a way that is portable across environments while avoiding hardcoded endpoints, indexes, table targets, or credentials.
Here, Agent1 uses:
a Dataverse table: CustomerOrders
an Azure AI Search index: customer-knowledge
Because each environment has its own Dataverse tables and Azure AI Search index, the deployment package should not carry over the development environment's live connections as fixed production settings. Instead, it should carry the agent and the references needed so the target environment can bind to its own production resources.
That is why the correct recommendation is:
Deployment package: Agent1 and references to the data sources
After deployment: Reconfigure the environment variables
Why this is correct:
Environment variables are the standard ALM-friendly way to externalize settings like:
endpoints
index names
table references
connection-related values
This supports secure handling of credentials and endpoints
It also helps minimize downtime, because production values can be switched cleanly after import without rebuilding the agent Why the other choices are weaker:
Agent1 only would omit needed source references
The data sources only would not deploy the actual agent
Agent1 and the data source connections risks carrying environment-specific connection bindings Agent1, the data sources, and the data source connections is too tightly coupled to the source environment and is not the best ALM design for secure cross-environment deployment Reconfiguring only Dataverse or only Azure AI Search is incomplete because both can vary by environment Reconfiguring Agent1 configuration is broader and less precise than using environment variables
質問 # 85
A company uses Microsoft Dynamics 365 Finance for accounts payable and customer debt recovery. You are designing an Al finance process that meets the following requirements:
Provides Al-driven details to help staff identify overdue vendor invoices and outstanding balances Helps staff reduce how long it takes to review overdue invoices and payment history You need to recommend which Microsoft Copilot features to include in the design.
What should you recommend for each requirement? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
正解：
解説：
Explanation:
Vendor overdue invoices and outstanding balances # AI Summaries with Copilot Review overdue invoices and payment history faster # Collections coordinator summary This question combines two different finance-process needs inside Dynamics 365 Finance:
The first requirement is in the accounts payable / vendor context. Staff need AI-driven details to quickly understand overdue vendor invoices and outstanding balances. The best fit is AI Summaries with Copilot, because this feature is intended to surface concise, contextual summaries that help users understand finance records faster without manually opening and reviewing every transaction.
The second requirement is in the customer debt recovery / collections context. Staff need to reduce the time spent reviewing overdue invoices and payment history. The best match here is Collections coordinator summary, because it is specifically aligned to collections work and helps users quickly review the customer's collections status, invoice aging, and payment-related context.
Why the other options are less suitable:
Agent management is administrative and not the feature that provides invoice/balance insights.
The Account Reconciliation agent is more focused on reconciliation tasks than on these specific AP and collections-review needs.
The supplier Communication agent is oriented toward supplier interaction/communication, not primarily summarizing overdue invoice and balance insight for internal review.
Analyze demand plans with Copilot is unrelated to overdue invoices or payment-history review.
質問 # 86
A company has a Microsoft Dynamics 365 Sales environment that has Microsoft Copilot enabled.
You need to customize Copilot by tailoring how opportunity summaries are generated or how they are presented to users.
Solution: You add the opportunity summary widget to the Opportunity form. Does this meet the goal?
正解：A
解説：
Adding the opportunity summary widget to the Opportunity form can make the summary visible in the user interface, but it does not tailor how the summary is generated, nor does it meaningfully customize its presentation logic beyond placement.
The question asks whether this meets the goal of customizing Copilot by tailoring:
* how opportunity summaries are generated, or
* how they are presented to users
Simply placing the widget on the form is more of a UI inclusion step than a true customization of Copilot summary behavior or rendering logic.
質問 # 87
Scenario: A development team is building a complex, multi-step agent using the Microsoft Agent Framework. This agent needs to receive a high-level user request, break it down into the required sequence of internal API calls and knowledge base, and manage the execution flow of these steps to achieve the final outcome.
Within the Agentic Core, which specific sub-component is primarily responsible for analyzing the user's intent, determining the optimal sequence of required tools/APIs and data sources (RAG), and managing the logical execution flow of these steps?
正解：D
解説：
The Planner and Orchestrator is correct because this component is the "brain" of the Agentic Core. Its function is to take the user prompt, use the LLM to assist in decomposition, build a logical plan (Planner) of steps to solve the request, and then manage the execution of those steps using the available Tools and data sources (Orchestrator).
References:
https://learn.microsoft.com/en-us/agent-framework/media/agent.svg
https://techcommunity.microsoft.com/blog/educatordeveloperblog/ai-agents-planning-and- orchestration-with-the-planning-design-pattern---part-7/4399204
https://www.microsoft.com/en-us/microsoft-365/planner/microsoft-planner
質問 # 88
Note: This section contains one or more sets of questions with the same scenario and problem. Each question presents a unique solution to the problem. You must determine whether the solution meets the stated goals. More than one solution in the set might solve the problem. It is also possible that none of the solutions in the set solve the problem.
After you answer a question in this section, you will NOT be able to return. As a result, these questions do not appear on the Review Screen.
A key stakeholder in your organization is championing the immediate deployment of Microsoft Copilot across all business units. Their primary justification is the belief that AI will automatically generate superior, data-driven decisions starting on day one, irrespective of the current state of organizational data quality or the alignment of existing business processes. You are tasked with providing an accurate assessment of this claim based on industry guidance, particularly Microsoft's "AI for Business" principles.
Based on Microsoft's "AI for Business" guidance, can you confidently state that deploying AI tools like Copilot will lead to better decisions with having a foundation of quality business data and well- defined, aligned workflows first?
正解：A
解説：
While Microsoft's "AI for Business" guidance indeed emphasizes that AI can enable better decision-making, it critically states that this capability is not automatic or instantaneous. Instead, it explicitly requires several foundational elements:
Processing large volumes of relevant, quality business data: AI tools like Copilot depend heavily on access to accurate, comprehensive, and well-structured organizational data to derive meaningful insights. Without quality data, the AI lacks the necessary inputs to provide intelligent, contextual, or reliable outputs.
Uncovering patterns: AI's strength lies in identifying patterns and correlations within data that human analysis might miss. This process is futile if the underlying data is incomplete, inaccurate, or unstructured.
Aligning the technology to business workflows: For AI-generated insights to translate into genuinely "better decisions," they must be integrated into and relevant to existing business processes. Deploying AI in a vacuum, without considering how it fits into and enhances current workflows, will diminish its practical value and impact on decision-making.
Therefore, deploying AI tools like Copilot without an existing foundation of quality data and aligned processes will not automatically guarantee improved decisions. The AI will lack the essential context and reliable inputs needed to generate meaningful insights and drive effective outcomes.
References:
https://www.microsoft.com/en-in/microsoft-copilot/copilot-101/ai-for-
business#Customerexperience
https://www.microsoft.com/en-in/microsoft-365/business-insights-ideas/resources/grow-your- small-business-with-artificial-intelligence
質問 # 89
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