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| Section | Weight | Objectives |
|---|---|---|
| Create intelligent applications | 25-30% | - Create canvas apps
|
| Create a foundation for intelligent applications | 25-30% | - Design Microsoft Power Platform solutions using AI-enabled tools
|
| Build business application logic and automation | 40-45% | - Business logic
|
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NEW QUESTION # 41
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: C
Explanation:
Assigning the appropriate security roles is the complete action because model-driven app access and Dataverse data access are both role driven. The app must be shared with the role, and the role must grant the accounting team the table privileges required to read and create or update the financial records. Configuring app visibility privileges alone may make the app tile appear, but it does not establish the underlying table rights. Setting an app as default affects navigation or launch preference and does not grant access. Granting table-level permissions is only one part of the required configuration and, in Dataverse, those privileges are normally delivered through a security role; option C represents the combined mechanism expected by the question. The administrator should use least privilege, choose the correct access depth, and include privileges for dependent tables and processes used by the app. Existing visibility in the launcher is not proof of effective authorization. The AB-410 Study Guide includes both "configure access to model-driven apps" and
"configure security." Appropriate role assignment aligns the user, the shared app, and the table operations in one enforceable access model.
Study Guide reference/topic: "Create model-driven apps - Configure access to model-driven apps." AB-410 Study Guide | Microsoft Learn technical reference
NEW QUESTION # 42
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: A,D,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 # 43
A company maintains a Power Platform solution that includes prompts, cloud flows, and Dataverse components. Multiple development teams are responsible for different features within the solution.
The development teams have the following requirements:
- Teams must develop and update the same features independently.
- Updates must not overwrite changes made by other teams.
- Production deployments must remain controlled and predictable.
You need to recommend an ALM approach that supports independent development and controlled deployment in line with Microsoft best practices.
What should you recommend?
Answer: A
Explanation:
Isolation prevents overwrites: Giving each team a separate development environment ensures they can build, edit, and test their features independently. It completely eliminates the risk of one team accidentally overwriting or breaking another team's components (like shared Cloud Flows or Dataverse tables) during active development.
Controlled production deployment: Deploying components as managed solutions into the production environment is a strict Microsoft ALM best practice. Managed solutions protect the target environment from unauthorized direct edits and allow for clean, predictable updates and rollbacks.
True parallel development: Segmenting features into individual solutions across isolated environments enables distinct release cadences for each development team.
References:
https://learn.microsoft.com/en-us/power-platform/alm/organize-solutions
NEW QUESTION # 44
A company is building a prompt about product specifications. The company plans to use the prompt in Power Automate.
The prompt must use Retrieval-Augmented Generation to ground the model with additional business information.
You need to select the available knowledge source for the prompt.
What should you use?
Answer: B
Explanation:
Dataverse table columns are the appropriate knowledge source for a prompt that must use Retrieval- Augmented Generation with current business information. Grounding the prompt with selected Dataverse data allows the model to incorporate governed product specifications at runtime instead of relying only on its pretrained knowledge. The maker can identify the relevant table and columns and then pass or retrieve the business context required by the prompt. A PNG image is an input artifact, not the structured knowledge source needed for specification retrieval. Plain text can provide fixed instructions or context but does not create a maintained enterprise data source. A PDF can be useful in other grounding experiences, but under the available prompt knowledge options in this scenario, the Dataverse table provides the direct, structured, updateable source. Access remains subject to environment and table security, so only approved data should be exposed to the prompt. The AB-410 Study Guide explicitly measures the ability to "add knowledge to a prompt." Selecting Dataverse table columns implements that objective while minimizing duplication of product data.
Study Guide reference/topic: "Create prompts and models in AI Hub - Add knowledge to a prompt." AB-
410 Study Guide | Microsoft Learn technical reference
NEW QUESTION # 45
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 implement a generative AI solution that meets the requirements.
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:
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 (starting from a blank prompt) for the template alignment, and a pre-built model for the complaint responses.
Task 1: Inspection Reports (Aligning to an Existing Template)
Approach: Start from a blank prompt (Custom Prompt).
Reason: Pre-built templates are rigid and designed for standard tasks like summarizing text or translating language. To make an AI output match your specific corporate inspection layout, tone, and data points, you need to write custom system instructions and ground it with your specific template rules.
Task 2: Customer Complaint Responses
Approach: Use a pre-built model (specifically the "Reply to a complaint" or "Create text with GPT" pre-built models in AI Builder).
Reason: Microsoft provides pre-trained, ready-to-use models optimized exactly for sentiment analysis and standard customer service drafting. This saves you from writing complex prompts from scratch for standard business scenarios.
Reference:
https://learn.microsoft.com/en-us/dynamics365/field-service/faqs-inspection-designer
NEW QUESTION # 46
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