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| Section | Weight | Objectives |
|---|---|---|
| Create a foundation for intelligent applications | 25-30% | - Design Microsoft Power Platform solutions using AI-enabled tools
|
| Create intelligent applications | 25-30% | - Create model-driven apps
|
| Build business application logic and automation | 40-45% | - Create cloud flows
|
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NEW QUESTION # 56
A company is building prompts in Microsoft Copilot Studio to support multiple customer service scenarios.
The company requires prompts to:
- Follow a consistent structure across use cases.
- Be reusable across multiple topics.
- Allow customization for different types of customer requests.
You need to build the prompts.
What should you do?
Answer: A
Explanation:
To best fulfill your requirements, you should create prompts by selecting templates from the prompt library and customizing them for each scenario.
The Microsoft Copilot Studio Prompt Library provides pre-built, standardized formats specifically designed to enforce a consistent structure. By taking a library-first approach and adding input/output parameters, you can build a modular system where a single base prompt is easily customized and reused across multiple topics.
Incorrect:
[Not A]
Configuring prompt model settings, on the other hand, only dictates the underlying LLM variant (e.g., GPT-4o) and generic runtime attributes, which does not solve for structural logic, reusability, or scenario customization.
Reference:
https://learn.microsoft.com/en-us/microsoft-copilot-studio/prompt-library
NEW QUESTION # 57
A company builds a canvas app to display and manipulate large datasets across multiple screens.
Users report the app takes a long time to load data when opened.
You need to optimize performance when the app is started.
What are three actions you can perform? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.
Answer: A,C,D
Explanation:
To optimize the startup performance of a Canvas app handling large datasets, you must focus on reducing the initial data payload and parallelizing operations.Here are three high-impact steps you can take:
[B] Remove data retrieval calls from App.OnStart:
Heavy data loading in App.OnStart blocks the app from rendering, forcing users to stare at a loading screen. Moving these calls to the OnVisible property of the first screen allows the UI to load immediately while data fetches in the background.
[D] Enable Concurrent Data Loading
By default, Power Apps loads data sources sequentially. You can use the Concurrent function in the App.OnStart or App.StartScreen property to load multiple collections or data sources at the exact same time. This dramatically reduces initial wait times.
[E] Use the ClearCollect() function to cache data: Storing large, frequently accessed datasets locally in a collection prevents the app from making repeated, slow network calls to the data source across multiple screens.
Reference:
https://learn.microsoft.com/en-us/power-apps/guidance/coding-guidelines/code-optimization
NEW QUESTION # 58
A company is designing a model-driven app for customer service representatives.
The app must:
# Organize navigation into logical groupings based on business processes.
# Ensure only required data is included in the app navigation.
You need to configure navigation and table availability.
Which actions should you perform? To answer, move the appropriate actions to the correct requirements. You may use each action once, more than once, or not at all. You may need to move the split bar between panes or scroll to view content. NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Logical navigation groupings - Customize the site map; Required tables in navigation - Add tables to app designer
The site map organizes a model-driven app's navigation into areas, groups, and subareas, so customizing it is the action that creates logical business-process groupings. Tables and other pages are exposed through those subareas. To ensure that only required table data is included, the maker adds the selected tables to the app in the app designer and omits unrelated tables. Configuring app settings changes runtime features and behavior but does not define the navigation hierarchy. App properties hold metadata such as name, description, or icon and likewise do not select the operational data components. The final app should be validated for dependencies because adding a table can also require forms, views, charts, and security-role privileges.
Navigation visibility does not itself grant data access; users still need the relevant Dataverse permissions. The Study Guide's model-driven app objectives include "compose a model-driven app" and configure its forms, views, and access. The correct mapping therefore uses the site map for information architecture and the app designer's table selection for component inclusion.
Study Guide reference/topic: "Create model-driven apps - Compose a model-driven app." AB-410 Study Guide | Microsoft Learn technical reference
NEW QUESTION # 59
A company plans to implement an automated process to retrieve and analyze customer feedback.
The company requires a solution that:
# Autonomously analyzes feedback.
# Stores results for reporting.
# Triggers an escalation for negative sentiment.
You need to design the solution.
Which three components should you use? Each correct answer presents part of the solution. NOTE: Each correct selection is worth one point. (Choose three.)
Answer: B,C,E
Explanation:
The solution requires an AI Builder prompt, a cloud flow, and a Dataverse table. The prompt performs the autonomous semantic analysis of each feedback item, including sentiment or other instructed classifications.
The cloud flow supplies the event-driven orchestration: it retrieves new feedback, calls the prompt, interprets the result, writes the output, and branches to an escalation action when sentiment is negative. Dataverse provides persistent, queryable storage for the original feedback, model result, status, and reporting fields. A canvas app may be useful for reviewing results but is not required for autonomous execution. A business rule can validate or adjust Dataverse data but cannot independently call the generative model and orchestrate external escalation. The flow should include explicit failure handling, confidence or result validation, and an idempotent design so retries do not create duplicate escalations. Approved data policies must also permit the connectors used by the flow. The Study Guide covers "consume a prompt in cloud flows," "configure cloud flow actions," and the creation of Dataverse-backed business solutions. A, B, and E form the complete analysis, automation, and persistence architecture.
Study Guide reference/topic: "Create cloud flows; Create prompts and models in AI Hub." AB-410 Study Guide | Microsoft Learn technical reference
NEW QUESTION # 60
A company creates an AI assistant that generates marketing content. Business users complain that responses vary significantly between identical requests. Which parameter should be adjusted?
Answer: C
Explanation:
Temperature controls randomness in generative AI output. Lower temperature values typically produce more consistent and predictable responses, while higher values increase creativity and variation. Storage, networking, and authentication settings do not influence model generation behavior. Adjusting temperature is a common method for controlling response consistency.
NEW QUESTION # 61
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