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| Section | Objectives |
|---|---|
| Build intelligent applications on Microsoft Power Platform | - Application development
|
| Embed agents and AI experiences | - Agent integration
|
| Design intelligent applications with Copilot and natural language | - AI-first application design
|
| Implement automation and orchestration | - Process automation
|
| Governance and application lifecycle management | - Responsible AI and ALM
|
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NEW QUESTION # 38
A company wants to build a generative AI assistant that answers employee questions using internal policies stored in SharePoint. The assistant must provide responses based only on approved company documents. Which architecture pattern should be implemented?
Answer: B
Explanation:
Retrieval-Augmented Generation (RAG) combines a language model with external knowledge retrieval. The system searches approved documents and provides relevant context to the model before generating answers. Fine-tuning changes model behavior but does not guarantee access to current information. RAG is preferred for enterprise assistants requiring grounded responses from organizational data sources.
NEW QUESTION # 39
A company uses Microsoft Dataverse to store customer records on the Account table. A business process flow is configured for the table.
The company requires a Power Automate cloud flow that validates and corrects the format of the customer account number. The Power Automate flow must run whenever data in this field changes.
You need to recommend a trigger for the cloud flow.
Which trigger should you recommend?
Answer: B
Explanation:
The cloud flow trigger should fire when a row is modified, specifically targeted to the Account table, with the "Select columns" (column filter) parameter set to the logical name of the customer account number column.
Correct Trigger Configuration
Connector: Microsoft Dataverse
Trigger: When a row is added, modified or deleted
Change type: Modified (or Added or Modified if you also need to check the format upon record creation) Table name: Accounts Reference:
https://learn.microsoft.com/en-us/power-automate/dataverse/overview
NEW QUESTION # 40
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:
Monitor remote execution - Use the Connect user feature; Retain session for review - Download the Monitor session file
The maker should use Monitor's Connect user feature to observe events from the remote user's live app session. The user opens the supplied connection, runs the problematic scenario, and Monitor streams network calls, formula evaluations, errors, and other diagnostics to the maker in near real time. This is preferable to attempting to reproduce a device- or account-specific issue locally. To retain evidence for later review or escalation, the maker downloads the Monitor session file. The file can be reopened and analyzed without requiring the user to repeat the failure. Test Studio automates test cases but does not attach to a remote interactive session. The App access checker diagnoses model-driven app entitlement rather than canvas-app runtime behavior. Application Insights can provide broader telemetry where instrumented, but it is not the required Monitor-session workflow in the answer area. Sensitive data visible in events should be handled according to organizational policy. The Study Guide explicitly lists "test canvas apps, including using Monitor." Connect user plus session download covers the live and retained-analysis requirements respectively.
Study Guide reference/topic: "Create canvas apps - Test canvas apps, including using Monitor." AB-410 Study Guide | Microsoft Learn technical reference
NEW QUESTION # 41
A company uses a canvas app to assign tasks to field workers.
Field workers must receive a notification when tasks are assigned.
The notification must be:
- Called from the app when a button is selected.
- Delivered as a mobile app notification.
You need to configure the notification.
Which three actions should you perform in sequence?
Exhibit:
Answer:
Explanation:
Explanation:
Add the Power Apps Notification connector # Configure the button ' s OnSelect property # Implement the SendPushNotification() function.
The Power Apps Notification connector enables canvas applications to send push notifications to users through supported Power Apps mobile applications. First, the maker adds the Power Apps Notification connector to the canvas app and configures the connection for the target application. Second, the OnSelect property of the relevant button is configured because this property executes actions when the user selects the button. Third, the SendPushNotification() function is implemented to send the notification to the assigned field worker. The function accepts information such as recipient identifiers, notification message content, and optional parameters for opening the target application. Recipients must have the supported mobile application installed, be signed in, and permit notifications on their devices. This configuration enables immediate, event- driven notifications directly from the canvas application without requiring a separate automated cloud flow.
NEW QUESTION # 42
A company builds a canvas app for support agents to enter customer notes and generate a summarized response by using a custom prompt.
The company requires the following functionality built into the prompt:
# Generate the summary immediately when the agent selects a button in the app.
# Supply current user-entered data to the prompt.
You need to execute the prompt.
Which two actions should you perform? Each correct answer presents part of the solution. NOTE: Each correct selection is worth one point.
Answer: A,B
Explanation:
The app should pass the current user-entered values as prompt parameters and invoke the prompt directly from the button's Power Fx logic. Parameters ensure that the generated summary is grounded in the text currently displayed in the app rather than stale or hard-coded data. Direct invocation from the button provides the immediate interactive behavior required by the scenario. A cloud flow can also consume a prompt, but it adds an orchestration layer that is u nnecessary when the requirement is limited to a synchronous canvas-app interaction. Publishing the prompt is part of making a completed component available, but it does not execute the prompt or provide the current input. Updating general app settings is unrelated. The button formula should validate blank content, handle errors, and place the returned summary in a variable or control only after a successful response. The prompt's inputs and output should be typed and tested for expected maximum lengths. The Study Guide explicitly includes "add inputs to a prompt" and "consume a prompt in apps." Options B and C meet those two runtime responsibilities.
Study Guide reference/topic: "Create prompts and models in AI Hub - Consume a prompt in apps." AB-410 Study Guide | Microsoft Learn technical reference
Topic 1, Fabrikam Inc
Background
Fabrikam Inc. is an energy provider that operates wind and solar farms across multiple countries and regions.
The company uses Microsoft Power Platform to manage asset maintenance, technician workflows, and predictive analytics.
Field technicians use canvas apps on mobile devices to capture inspection and repair data. Operations managers use model-driven apps to monitor asset performance and maintenance history.
The company plans to enhance its platform by introducing AI-driven insights, improving reuse across applications, and establishing a formal application lifecycle management (ALM) strategy.
Current environment
Applications
Field technicians use an outdated mobile app to log maintenance activities and capture asset readings in SharePoint Online.
Operations managers use a model-driven app to review maintenance records and asset performance trends.
Development practices
Developers build and modify applications directly in the production environment.
There is NO structured ALM process.
Solutions are NOT consistently used to package or deploy application components.
Reusable components are inconsistently implemented across apps, leading to duplication.
AI integration
Fabrikam Inc. plans to actively explore generative AI usage as part of the next phase of work.
Business requirement
Application development
The outdated mobile app must be replaced with a new app that supports responsive design principles, provides full control over the UI, and allows technicians to take and upload photos directly from their mobile devices.
The new app for the field technicians requires the name of the technician to be persisted on the home screen only. In addition, work orders must be displayed within a gallery.
All new apps must connect to a scalable, cloud-based relational data store.
Apps must support efficient data entry for technicians in the field.
Reusable UI elements must be implemented to reduce duplication.
AI capabilities
The company requires a generative AI solution to manage customer complaint responses and create custom inspection reports that align to an existing template.
Customer complaint responses must be generated in applications and based on emails being sent to a mailbox.
Custom AI development must be minimized.
Generative AI reusability
Generative AI solutions must accept dynamic inputs to adapt to different scenarios.
Generative AI solutions must be reusable across different Power Platform services.
Extensibility
Custom UI form components must be reusable across applications.
Use of server-side custom code must be minimized where possible.
Technical requirements
Application lifecycle management (ALM)
Separate environments must be used for development, testing, and production.
Solutions must be used to package application components, segmented based on functional areas.
Managed solutions must be deployed to the production environment.
Validation must occur before deployment to production.
Data processing
Aggregated values across related rows must be displayed for reporting.
Calculations must update automatically as new data is entered. Calculation data must be limited to a maximum length of 10.
Issues
Duplicate logic exists across multiple canvas apps.
Developers frequently overwrite changes in production.
Generative AI solutions produce inconsistent outputs due to missing or inconsistent inputs.
Maintenance metrics are not consistently calculated across related rows.
NEW QUESTION # 43
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