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Microsoft AB-410 Exam Syllabus Topics:

SectionObjectives
Embed agents and AI experiences- Agent integration
  • 1. Embed Copilot Studio agents into applications
  • 2. Build agent-first user experiences
Design intelligent applications with Copilot and natural language- AI-first application design
  • 1. Leverage natural language experiences in application development
  • 2. Use Copilot capabilities to design solutions
Governance and application lifecycle management- Responsible AI and ALM
  • 1. Implement responsible AI practices
  • 2. Apply governance and security controls
  • 3. Manage application lifecycle and deployment
Implement automation and orchestration- Process automation
  • 1. Coordinate apps, agents, and AI models
  • 2. Automate business workflows
Build intelligent applications on Microsoft Power Platform- Application development
  • 1. Create AI-powered business applications
  • 2. Integrate AI models into applications

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Microsoft Building Intelligent Applications Sample Questions (Q71-Q76):

NEW QUESTION # 71
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: B,D,E

Explanation:
The app should remove avoidable retrieval work from App.OnStart, enable supported preloading, and run independent retrieval calls with Concurrent. App.OnStart executes before the user can interact with the app; large or sequential data operations there directly extend startup time. Moving work to named formulas, screen- level loading, or on-demand execution allows the shell to become usable sooner. Preloading prepares supported app resources and data behavior ahead of use, reducing perceived delay where the setting applies.
Concurrent evaluates independent formulas at the same time rather than serially, so total wait time approaches the longest individual call instead of the sum of all calls. Moving transformations from the source into Power Fx can reduce delegation and force more records onto the client, which usually harms performance.
ClearCollect can cache a bounded dataset, but loading a large dataset into a collection at startup is precisely the pattern the scenario needs to reduce. The corrected answer is B, C, and D. This aligns with the Study Guide objective to design canvas apps for "performance" and with Microsoft guidance to minimize App.
OnStart dependencies and parallelize independent operations.
Study Guide reference/topic: "Create canvas apps - Design apps for performance." AB-410 Study Guide | Microsoft Learn technical reference


NEW QUESTION # 72
Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.
After you answer a question in this section, you will NOT be able to return to it. As a result these questions will not appear on the review screen.
A company integrates external systems into Power Automate by using cloud flows.
The company must connect to external services with different characteristics and determine whether a custom connector is required.
You need to evaluate if a custom connector is necessary to meet the requirements.
Solution: A cloud flow must call a REST API by using a one-time HTTP action without reuse across flows.
Does the solution meet the goal?

Answer: B

Explanation:
Correct:
* A cloud flow must integrate with an internal web service that is used across multiple flows and requires reusable actions.
This scenario requires a custom connector. Because it is a proprietary or internal service, Microsoft does not provide a pre-built native bridge. Building a Microsoft Custom Connector wraps the web service's REST/SOAP API into a reusable tool, eliminating the need to repeatedly configure HTTP headers and endpoints across separate flows.
Incorrect:
* A cloud flow must call a REST API by using a one-time HTTP action without reuse across flows.
A custom connector is not necessary here. For single-use or non-reusable integrations, using a generic built-in HTTP action step is the most efficient and fastest choice.
* A cloud flow must retrieve data from Microsoft Dataverse.
Power Automate includes a native, out-of-the-box Microsoft Dataverse connector. There is no need to develop a custom connector for default Power Platform data storage.
* A cloud flow must retrieve data from SharePoint Online lists.
SharePoint Online is fully supported by native Microsoft 365 integrations. You should use the pre- built SharePoint connector instead of creating a custom wrapper.
Reference:
https://alphavima.com/blog/power-apps-custom-connector-rest-api/


NEW QUESTION # 73
A company uses a Dataverse table to manage support cases.
You must provide employees with a summary of case information derived from multiple columns without requiring a manual review of the data.
The solution has the following requirements:
# Generate a case summary following the given instructions.
# Include the context of the current record in the generated output.
You need to configure the solution.
Which two actions should you perform? Each correct answer presents part of the solution. NOTE: Each correct selection is worth one point.

Answer: B,D

Explanation:
The maker should define a prompt that references the support-case fields and create the destination column with the Prompt data type. The prompt contains the instructions for producing the case summary and declares the record inputs needed to ground that output. The prompt column then makes the generated summary available in the Dataverse/model-driven app context for the current row. A formula column performs deterministic Power Fx computation and cannot generate a natural-language summary from multiple fields. A business rule can set or validate values, but it does not invoke a generative model. The prompt should limit inputs to the approved columns, specify the required structure, and handle empty or contradictory case data so the generated content remains useful. Security on the source fields must still be respected, because an AI- generated summary must not become a route around restricted data. The AB-410 Study Guide lists "configure prompt columns" under Build data models and "add inputs to a prompt" under AI Hub. Options A and D supply the instruction definition and the Dataverse column behavior required for record-context generation.
Study Guide reference/topic: "Build data models - Configure prompt columns." AB-410 Study Guide | Microsoft Learn technical reference


NEW QUESTION # 74
Hotspot Question
A remote Power Apps user experiences an issue with a canvas app. The issue cannot be reproduced locally.
You must analyze the issue in near real-time. Session data must be available for later review.
You need to troubleshoot the canvas app by using Monitor.
How should you troubleshoot the app? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Explanation:
Box 1: Use the Connect user feature
To capture a remote user's canvas app session in near real-time, use the Connect user feature in Power Apps Live monitor overview Collaborative troubleshooting using Live monitor. This allows you to generate a secure join link for the user, intercepting their specific actions as they happen Collaborative troubleshooting using Live monitor.
Box 2: Download the Monitor session file
To share a troubleshooting session for later review using Power Apps Monitor, you must use the Connect user feature to capture the remote session, and then click Download to save the session log as a JSON file. This downloaded file can then be shared and uploaded into Monitor by another team member at any time for offline analysis.
Reference:
https://learn.microsoft.com/en-us/power-apps/mobile/powerapps-mobile-troubleshoot


NEW QUESTION # 75
An organization deploys an AI application handling customer information. The company must ensure transparency regarding AI-generated decisions and provide explanations to users. Which responsible AI principle applies?

Answer: B

Explanation:
Transparency is a responsible AI principle focused on explaining how AI systems operate and how decisions are produced. Users should understand when AI is involved and receive appropriate information about outcomes. Hardware optimization and compression improve technical performance but do not address ethical requirements or user understanding.


NEW QUESTION # 76
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