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| Section | Objectives |
|---|---|
| Build intelligent applications on Microsoft Power Platform | - Application development
|
| Governance and application lifecycle management | - Responsible AI and ALM
|
| Implement automation and orchestration | - Process automation
|
| Design intelligent applications with Copilot and natural language | - AI-first application design
|
| Embed agents and AI experiences | - Agent integration
|
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NEW QUESTION # 73
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Field technicians use an outdated mobile app to log maintenance activities and capture asset readings in SharePoint Online.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The outdated mobile app must be replaced with a new app that supports responsive design principles, provides full control over the UI, and allows technicians to take and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 provide a solution for field technicians to create custom inspection reports natively within the new app. What should you do?
Answer: C
Explanation:
Scenario: The company requires a generative AI solution to manage customer complaint responses and create custom inspection reports that align to an existing template.
You should use a custom prompt.
Generative AI Capability: Power Platform AI Builder prompts leverage large language models (like GPT) to natively handle generative text workflows.
Complaint Handling: A custom prompt can be built specifically to analyze customer feedback and automatically generate draft email or text responses.
Template Alignment: You can embed your exact inspection report layout and instructions directly inside the custom prompt's logic. This ensures that the generated outputs perfectly match the structure of your existing template.
Reference:
https://learn.microsoft.com/en-us/ai-builder/overview
NEW QUESTION # 74
An accounting team is assigned to a model-driven app to manage financial data.
The app is currently visible in the app launcher but inaccessible to the accounting team.
Users must be able to:
- Open the app.
- Access and record financial data.
You need to resolve the access issues.
What should you do?
Answer: D
NEW QUESTION # 75
A company builds a canvas app that processes images submitted by users and must classify them using an existing AI Builder model.
The app must generate predictions during user interaction.
You need to consume the AI model natively.
What should you do?
Answer: B
Explanation:
The app should call the existing AI Builder model from its app logic. The model is added to the canvas app and invoked from Power Fx associated with a user event such as a button selection, passing the current image as input. The returned class, confidence, or other prediction values can immediately update controls or be stored with the business record. Retraining for every image is neither required nor operationally appropriate; training is a controlled model-lifecycle activity performed with a curated dataset. Reusing a stored prediction would classify the previous input rather than the newly submitted image. Exporting a solution transports the model and app components between environments but does not execute inference. Runtime code should check that an image exists, handle prediction failures, and apply a confidence threshold or human-review path where the business decision requires it. The AB-410 Study Guide includes the exact objective "consume an AI model in apps." Option D describes that native runtime consumption and is the only action that generates a prediction during the user's current interaction.
Study Guide reference/topic: "Create prompts and models in AI Hub - Consume an AI model in apps." AB-
410 Study Guide | Microsoft Learn technical reference
NEW QUESTION # 76
Drag and Drop Question
A company processes transaction records by using a Power Automate cloud flow.
The company has the following requirements:
- Continue processing records until a status field changes to Complete, even if new records are added during execution.
- Process a fixed list of records retrieved at the start of the flow,
ensuring each record is processed exactly once.
You need to configure the flow control logic.
Which controls should you use? To answer, move the appropriate controls to the correct requirements. You may use each control 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: Do until
A Do Until control logic is perfectly suited for this Power Automate cloud flow requirement. It allows the flow to continuously loop and process records dynamically, meaning if new items are continuously added to the queue during execution, the loop will catch and process them as long as the data is retrieved dynamically inside every iteration.
Box 2: Apply to each
Use the "Apply to each" control action. It takes the fixed array (list of records) you retrieved at the start of your flow and processes the records one by one.
Reference:
https://learn.microsoft.com/en-us/azure/logic-apps/logic-apps-control-flow-loops
https://learn.microsoft.com/en-us/power-automate/apply-to-each
NEW QUESTION # 77
A company processes transaction records by using a Power Automate cloud flow.
The company has the following requirements:
# Continue processing records until a status field changes to Complete, even if new records are added during execution.
# Process a fixed list of records retrieved at the start of the flow, ensuring each record is processed exactly once.
You need to configure the flow control logic.
Which controls should you use? To answer, move the appropriate controls to the correct requirements. You may use each control 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:
Continue until status is Complete - Do until; Process the fixed retrieved list - Apply to each
Do until is the correct loop when processing must continue until a runtime condition becomes true. The flow can recheck the status and repeat its actions until Status equals Complete, subject to configured count and timeout limits. Because the condition is reevaluated between iterations, it can respond to a status change that occurs while the flow is running. Apply to each is correct for the fixed array of records retrieved at the beginning. It enumerates each item in that array once; records added to the source later are not automatically inserted into the already obtained collection. Scope groups actions for error handling or organization but does not implement either iteration pattern. Concurrency settings affect parallelism and ordering within a loop but do not replace the loop itself. The Do until design should include a delay or appropriate polling interval and explicit termination safeguards to avoid excessive requests. Apply to each concurrency should be chosen according to ordering and connector limits. The Study Guide's cloud-flow objectives include "implement flow control with conditions and loops." The verified mapping matches a condition-driven loop and a collection-driven loop to their intended behaviors.
Study Guide reference/topic: "Create cloud flows - Implement flow control with loops." AB-410 Study Guide | Microsoft Learn technical reference
NEW QUESTION # 78
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