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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Create intelligent applications | 25-30% | - Create model-driven apps
|
| Topic 2: Create a foundation for intelligent applications | 25-30% | - Build data models in Dataverse
|
| Topic 3: Build business application logic and automation | 40-45% | - Business logic
|
>> AB-410 Latest Exam Materials <<
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NEW QUESTION # 43
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Field technicians use an outdated mobile app to log maintenance activities and capture asset readings in SharePoint Online.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The outdated mobile app must be replaced with a new app that supports responsive design principles, provides full control over the UI, and allows technicians to take and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 configure the generative AI reusability requirements. What should you do?
Answer: A
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.
To achieve the requirement of managing customer complaint responses and creating custom inspection reports that align with a specific template, you should Call the prompt from a Power Automate cloud flow.
Automated Document Generation: Generating an inspection report matching an existing template requires background document-generation engines, file handling, and saving capabilities (e.g., population into SharePoint, Word Online, or OneDrive). Power Automate is specifically engineered to orchestrate these multi-step background enterprise automations.
Multi-Step Workflow Orchestration: A single automated cloud flow can naturally string together multiple tasks sequentially. For instance, it can ingest incoming data, run the AI Builder Run a prompt action to draft the empathetic complaint response, use a second prompt action to structure the template report, and then distribute both as needed.
Human-in-the-Loop Capabilities: Microsoft highly recommends adding human oversight for generative AI outputs in complaint responses before sending them to customers. Cloud flows make it easy to seamlessly pause mid-process and use Power Automate Approvals to let a human review the content.
Reference:
https://learn.microsoft.com/en-us/ai-builder/use-a-custom-prompt-in-app
NEW QUESTION # 44
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: D
Explanation:
Separate development environments and separate solutions provide the required isolation between teams, while managed deployments provide production control. Each team can own a functionally scoped solution in its own development environment, preventing concurrent makers from overwriting the same unmanaged component layer. The solutions can be source-controlled, validated, and deployed independently through an approved pipeline. Importing them as managed solutions in production gives the organization a controlled, upgradeable package and supports removal through solution uninstall when dependencies permit. Keeping separate solutions in one shared development environment does not fully isolate changes to common components. Direct changes in production bypass validation and make the deployed state difficult to reproduce. Unmanaged solutions in production merge customizations into the active layer and are not the recommended release artifact. Dependencies and shared components must still be planned deliberately so that one solution does not silently require another team's unmanaged work. This approach reflects the Study Guide requirement to "apply a Microsoft Power Platform solution and ALM strategy" and the standard separation of development, test, and production responsibilities.
Study Guide reference/topic: "Design Power Platform solutions - Apply a solution and ALM strategy." AB-
410 Study Guide | Microsoft Learn technical reference
NEW QUESTION # 45
A company uses a canvas app to retrieve records from a large data source. Users report slow performance when searching and filtering data. The company requires a solution that:
* Improves performance when working with large datasets.
* Optimizes query execution.
* Enables the app to load quickly.
You need to optimize query performance. What should you do?
Answer: A
Explanation:
Deferring nonessential data loading reduces the amount of work performed during application startup and allows the first screen to become interactive sooner. Data that is needed only on later screens or after a user action should be queried when it is actually required. This avoids large OnStart collections, lowers memory consumption, and prevents unnecessary connector calls. Loading the entire dataset into a local collection is the opposite of the requirement and can hit row limits while creating long startup delays. Splitting the same large result across several collections still transfers excessive data and adds state-management complexity.
Server-side views can help constrain data, but the question ' s broad startup requirement is best addressed by delayed loading together with delegable Filter and Search formulas. Makers should use delegable predicates, request only needed columns, cache only small stable reference data, and verify behavior with App checker and Monitor. Microsoft recommends minimizing startup work and delaying noncritical calls as core canvas- app performance practices.
Reference: https://learn.microsoft.com/en-us/power-apps/maker/canvas-apps/efficient-calculations Study Guide alignment: Create intelligent applications.
NEW QUESTION # 46
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: D
Explanation:
The Microsoft Dataverse trigger "When a row is added, modified or deleted" is the correct trigger because the flow must run automatically whenever the Account Number field changes. The trigger can be configured for the Modified change type, the Account table, and an appropriate scope. Its Select columns or filtering- attributes setting should identify the account-number column so unrelated row updates do not start the validation flow. A trigger condition can further prevent work when the value is blank or already normalized.
"When a row is selected" is an instant, user-initiated trigger and does not run automatically. A business- process-flow step only runs when that step is explicitly invoked. "When an action is performed" responds to a defined Dataverse action rather than a standard column modification. The correction logic should also avoid recursively retriggering itself when it updates the formatted value, for example by comparing the existing and normalized values before writing. The Study Guide explicitly lists "recommend cloud flow triggers." Option D is the only event trigger that directly observes Dataverse row modification and can be narrowed to the required field.
Study Guide reference/topic: "Create cloud flows - Recommend cloud flow triggers." AB-410 Study Guide | Microsoft Learn technical reference
Topic 2, Contoso Ltd.
Background
Contoso Ltd. is a global renewable energy provider that operates wind farms and solar installations. The company is modernizing its maintenance and operations platform. The company plans to implement a Microsoft Power Platform solution for the operations team. The implementation will include Microsoft Dataverse, a model-driven app, and Power Automate cloud flows.
The company is building and testing a new model-driven app named Operations. The solution will support operations managers, regional coordinators, and field technicians. The app must integrate with an external cloud-based system that manages onboarding of field technicians.
Contoso Ltd. plans to improve data quality and enforce consistent business logic across the app and automation processes.
Technical environment
Contoso Ltd. has an Identity and Access Management (IDAM) department that manages security. The company has one Power Platform environment named Production, where all building and configuration take place. Auditing is disabled .
The Production environment has the following security configurations:
# IDAM has a Microsoft Entra security group named Contoso Ltd. QA. This security group will assign all members a Power Apps license.
# IDAM created a Quality Assurance security role that grants read and write access to all custom tables.
# IDAM also created a team named Testers in Dataverse, of a Microsoft Entra group team type. The team is configured for the Contoso Ltd. QA security group. The Testers team is assigned the Quality Assurance security role.
Microsoft 365 environment
All Contoso Ltd. managers are included in a Microsoft 365 group named Managers. The group is NOT enabled for email. The company shares a SharePoint list with a key customer: Alpine Ski House. Alpine Ski House staff members can add new maintenance requests, which are then checked and marked as reviewed by Contoso Ltd.
Current issue:
A new QA tester joins Contoso Ltd. The IDAM department adds the new tester to the Contoso Ltd. QA security group. However , the new tester is not listed in the Testers team as a member.
Other applications:
A separate software-as a-service (SaaS) solution named TechCheck manages technician onboarding .
The TechCheck solution is set up as follows:
# TechCheck assigns a unique number named Ref to all technicians.
# Users cannot make changes to the TechCheck data model.
# Users cannot use the same TechCheck ref on more than one Technician row.
Automation requirements
Contoso plans to use Power Automate to develop a Maintenance Request Approval flow .
The flow must meet the following requirements:
Create a Maintenance Request row in Dataverse when either of the following occurs:
# An item is added to the SharePoint list by the customer with the Priority property set to High.
# Any item is checked and marked as reviewed by a Contoso Ltd. representative.
Seek maintenance request approvals from managers through both email and a Microsoft Teams message after they have been reviewed:
# Requests require approval from all managers.
# If one manager rejects the request, approval must not be granted.
# The result of the approval request must be sent to the initial reviewer in an email.
# The subject line must set the response as either Approve or Reject.
Contoso Ltd. requires the following table logic:
# If a user tries to enter a price greater than the cost on a new Asset row, the row must display an inline error message.
# If a user tries to save changes to a Technician row where the TechCheck ref column is empty, the action must be prevented and a message explaining the action must be displayed.
# Any updates made to Technician profiles in TechCheck must be mirrored in Dataverse by using a custom integration. The developers building the integration require an index for performant searches on the Technician table.
Data model and app design
Contoso Ltd. plans to use Dataverse as its central data platform. Log storage must be minimized.
Tables
The following tables are required for data modeling and the app design:
# Assets: Stores information about solar panels and wind turbines
# Maintenance Requests: Tracks issues and maintenance activities.
The table must include the following columns:
# Request ID (auto-number)
# External Request Code (text)
Assigned
Technician (lookup to Technicians)
Report (lookup to Maintenance Reports)
Technician updated (Yes/No)
Maintenance Reports: Tracks the results of maintenance reports
Technicians: Stores technician assignment data .
The table must include the following columns:
# Full Name (Text)
# Mobile phone number (Text)
# Email (Text)
# Seniority (Choice)
# TechCheck ref (Text)
Data modeling
The data model must provide the following functionality:
Maintenance Requests must:
be uniquely identifiable across systems.
have two inactive statuses, Cancelled and Duplicate.
If a new option is added to an existing set of options, it must be made available automatically for selection on all columns that use the set.
A new column named Priority must be added to multiple tables .
Users must be able to select only one option from the following set per row:
- Low
- Medium
- High
- Critical
Changes to the Technician column on Maintenance Requests must be tracked for compliance purposes. Rows must include the names of previous and current technicians and the time of the change.
Relationship requirements
One asset can be related to many maintenance requests. A maintenance request can have many assets.
A maintenance request can have only zero or one maintenance report.
Only one Technician can be related to a Maintenance Request at a time.
When a Maintenance Request is deleted, any Maintenance Reports associated with it must also be deleted, but this action should be prevented if there is value in the Technician lookup.
When a Maintenance Request is assigned to a different owner, the Maintenance Report associated with it must be reassigned to the new owner as well, but the associated Technician should stay with the current owner.
App design
The Technicians table contains the following public views:
- Senior Technicians
- Junior Technicians
The Senior Technician view must be available through the table list view selector to a set of specific users only.
A tester creates a personal view named Hot Assets on the Assets table. The tester recognizes that the view is useful for the entire testing team. The view must be made accessible to the team.
NEW QUESTION # 47
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: D
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 # 48
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