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| Section | Weight | Objectives |
|---|---|---|
| Extend and secure intelligent solutions | 20% | - Secure access and data
|
| Build intelligent apps with Copilot and agents | 30% | - Create and manage agents with Copilot Studio
|
| Create a foundation for intelligent applications | 28% | - Implement responsible AI principles
|
| Enhance solutions with AI and automation | 22% | - Build automation with Power Automate
|
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NEW QUESTION # 47
Case Study 2 - 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Field technicians use an outdated mobile app to log maintenance activities and capture asset readings in SharePoint Online.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The outdated mobile app must be replaced with a new app that supports responsive design principles, provides full control over the UI, and allows technicians to take and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.
You need to resolve the issues with the canvas apps.
Which two configurations should you use? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.
Answer: A,C
Explanation:
Scenario: Duplicate logic exists across multiple canvas apps.
The two features that can be used to remedy the problem of duplicate logic existing across multiple canvas apps are component library and User defined function.
Component library: This feature allows you to build reusable canvas components (containing both visual elements and custom properties with calculation or behavioral logic) and host them centrally. Multiple canvas apps can then import these components from the library, providing a single source of truth that simplifies maintenance across your entire app ecosystem.
User defined function (UDF): This Power Fx feature enables you to write a custom formula once, complete with input parameters and an output data type. By packaging this pure behavioral or calculation logic into an enhanced component property within a component library, the custom function can be called globally across multiple apps Reference:
https://learn.microsoft.com/en-us/power-apps/maker/canvas-apps/working-with-large-apps
NEW QUESTION # 48
Maintenance metrics are not consistently calculated across related rows.
You need to provide a solution for field technicians to create custom inspection reports natively within the new app.
What should you do?
Answer: C
Explanation:
A custom prompt is the native low-code mechanism for generating an inspection report from current app data while following the company's existing template instructions. The maker can define inputs for the inspection fields, specify required sections, tone, order, and formatting, and invoke the prompt from the new app. This keeps the report-generation experience within Power Platform and minimizes custom AI development. A paginated report is well suited to deterministic, pixel-precise reporting, but it does not perform the requested generative composition and generally presents a separate reporting artifact. A Word template performs deterministic field substitution and is useful when no generative rewriting is required; it does not supply the AI-driven custom narrative described in the case. The prompt should be grounded only with approved inspection data, tested for missing inputs, and reviewed for output consistency before production use. The Study Guide covers "build prompts," "add inputs to a prompt," and "consume a prompt in apps." Option C is therefore the component that directly implements native generative inspection-report creation.
Study Guide reference/topic: "Create prompts and models in AI Hub - Consume a prompt in apps." AB-410 Study Guide | Microsoft Learn technical reference
NEW QUESTION # 49
Drag and Drop Question
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:
Box 1: Customize the site map
To organize navigation into logical groupings based on business processes in a model-driven app, you must configure the App's Sitemap by adding Areas, Groups, and Subareas.
Box 2: Add tables to app designer
App Designer Includes Data: Adding tables directly to the app designer makes them part of the app's underlying data model and security scope, but it does not automatically place them in the navigation menu.
Reference:
https://learn.microsoft.com/en-us/power-apps/maker/model-driven-apps/create-site-map-app
NEW QUESTION # 50
A company uses a prompt to generate responses based on internal support knowledge.
The company requires the prompt to minimize generation of unsupported and incorrect information while ensuring responses remain useful.
You need to tune the prompt model settings.
How should you configure the model settings?
Answer: D
Explanation:
Decreasing temperature makes the model's output more deterministic and less exploratory. For a support- knowledge prompt, that reduces variation and lowers the probability that the model invents unsupported wording when the same grounded information is supplied. Increasing temperature would encourage broader token selection and is counter to the requirement for reliable, repeatable answers. Content moderation level addresses detection or blocking of potentially harmful material; it is not the primary control for factual grounding or generation variance. Increasing moderation can be appropriate for safety policy, but it does not make a response more faithful to the internal knowledge source. The prompt should also contain precise instructions, approved grounding content, explicit handling for missing information, and a direction not to infer facts that are absent. Temperature is one control within that broader prompt-quality design. The Study Guide includes "customize prompt settings, including models" and "add knowledge to a prompt." Option C is the model-setting change that directly supports stable, conservative generation while retaining useful grounded responses.
Study Guide reference/topic: "Create prompts and models in AI Hub - Customize prompt settings." AB-410 Study Guide | Microsoft Learn technical reference
NEW QUESTION # 51
A company uses a model-driven app to enforce data quality standards.
The company requires the following app functionality:
# Ensure users enter a value in a specific column when a condition is met.
# Prevent users from saving the record until they complete the field.
The solution must be implemented without using code or automation.
You need to configure a business rule to meet the requirements.
What should you do?
Answer: D
Explanation:
The business rule should use Set requirement level to make the target column Business Required when the stated condition is true. In a model-driven form, this prevents the record from being saved until a value is entered, and the requirement can be returned to Optional when the condition no longer applies. Show recommendation presents advisory guidance that a user may ignore, so it cannot enforce completion. Set field visibility only controls whether a control is displayed. Set default value supplies an initial value but does not guarantee that a valid value remains or that the user cannot clear it. The rule should be scoped to the intended table or form and should include both the true and false paths so requirement level does not remain incorrectly set after values change. If the rule must govern updates through APIs as well as forms, the designer must confirm that the selected scope and action provide server-side enforcement for the scenario. The Study Guide explicitly lists "configure business rules." Option D is the declarative, no-code action that implements conditional mandatory data entry and blocks the form save until the requirement is satisfied.
Study Guide reference/topic: "Implement business and process logic - Configure business rules." AB-410 Study Guide | Microsoft Learn technical reference
NEW QUESTION # 52
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