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Microsoft AB-410 Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Topic 1: Governance and application lifecycle management | - Responsible AI and ALM
|
| Topic 2: Build intelligent applications on Microsoft Power Platform | - Application development
|
| Topic 3: Design intelligent applications with Copilot and natural language | - AI-first application design
|
| Topic 4: Embed agents and AI experiences | - Agent integration
|
| Topic 5: Implement automation and orchestration | - Process automation
|
Microsoft Building Intelligent Applications Sample Questions:
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Field technicians use an outdated mobile app to log maintenance activities and capture asset readings in SharePoint Online.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The outdated mobile app must be replaced with a new app that supports responsive design principles, provides full control over the UI, and allows technicians to take and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.
- A. Collection
- B. Named formula
- C. User-defined function
- D. Context variable
- E. Component library
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A company develops an AI chatbot using Azure OpenAI. Security administrators require that customer data must not be used to train public foundation models. Which statement correctly describes Azure OpenAI data handling?
- A. Customer prompts automatically train OpenAI public models
- B. Customer data remains isolated from public model training
- C. All prompts are shared with external users
- D. Fine-tuning data becomes publicly searchable
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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 in the review screen.
You administer the Microsoft 365 and Microsoft Power Platform environments for Contoso, Ltd.
The company has a model-driven app that is used to track customer interactions with employees.
The app uses standard table types for customers. A user named Elisabeth Rice signs in to the app by using the following sign in name: [email protected].
After marriage, Elisabeth changes her legal name to Elisabeth Mueller.
You need to update the sign in name for the user without losing any application history.
Solution: Ask the Microsoft 365 administrator to sign in to the admin portal and change the user name.
Does the solution meet the goal?
- A. No
- B. Yes
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An organization wants to deploy an AI application that identifies defective products from manufacturing camera images. The company has thousands of labeled images and requires a customized model with continuous retraining capabilities. Which Azure service should be used?
- A. Azure AI Language
- B. Azure Machine Learning
- C. Azure Bot Service
- D. Azure AI Vision image analysis
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Drag and Drop Question
An insurance company is implementing a customer service solution in Microsoft Dataverse to track interactions and manage issue resolution. The data model includes tables for customer information, support cases, and agents.
The data model includes the following requirements:
- Link each support case to a customer.
- Provide information on the children of customers.
- Record history of agents assigned to customers.
You need to configure table relationships.
Which relationships should you use? To answer, move the appropriate relationship to the correct requirement. You may use each relationship 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.
Explanation:
Box 1: One-to-many
To link each support case to a specific customer in Microsoft Dataverse, you should use a One- to-many (1:N) relationship. This allows one customer (Account or Contact) to be associated with multiple support cases over time, while each individual case is linked to exactly one customer.
Box 2: One-to-many
You should use a One-to-many relationship.
Parent to Children: One customer (parent) can have multiple children.
Child to Parent: Each child belongs to only one customer (parent) in this specific structural context.
Note: Both the children parents could be customers, in which case a many-to-many relation could be considered.
Box 3: Connections
To record a history of multiple agents assigned to multiple customers over time, you should use Connections.
Tracks Historical Data: Standard Dataverse relationships (like One-to-Many) only show the current assignment. Connections let you keep a running log of past and present relationships.
Many-to-Many Behavior: An agent can be linked to many customers, and a customer can have many agents over time.
Adds Context: Connections allow you to assign "Connection Roles" (e.g., "Primary Agent,"
"Backup Agent," "Former Agent") and include start/end dates for when the agent was assigned.
Reference:
https://learn.microsoft.com/en-us/power-apps/maker/data-platform/create-edit-entity-relationships
https://learn.microsoft.com/en-us/power-apps/developer/data-platform/connection-entities
