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| Section | Weight | Objectives |
|---|---|---|
| Enhance solutions with AI and automation | 22% | - Build automation with Power Automate
|
| Build intelligent apps with Copilot and agents | 30% | - Integrate Copilot into canvas and model-driven apps
|
| Create a foundation for intelligent applications | 28% | - Implement responsible AI principles
|
| Extend and secure intelligent solutions | 20% | - Secure access and data
|
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NEW QUESTION # 25
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?
Answer: C
Explanation:
Azure Machine Learning provides tools for developing, training, deploying, and managing custom machine learning models. Because the organization has labeled images and requires continuous retraining, a custom ML workflow is appropriate. Azure AI Vision offers prebuilt capabilities but is less suitable when specialized industrial image recognition models must be trained and optimized.
NEW QUESTION # 26
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 on the review screen.
A company integrates external systems into Power Automate by using cloud flows.
The company must connect to external services with different characteristics and determine whether a custom connector is required.
You need to evaluate if a custom connector is necessary to meet the requirements.
Solution: A cloud flow must retrieve data from Microsoft Dataverse.
Does the solution meet the goal?
Answer: B
Explanation:
Microsoft Dataverse is already supported by the first-party Microsoft Dataverse connector, so a custom connector is not necessary. The connector includes actions such as List rows, Get a row by ID, Add a new row, Update a row, and Delete a row, as well as triggers for row events. For retrieval, the maker chooses Get a row for a known identifier or List rows for a query and can apply select, filter, order, expand, and pagination options where supported. The connection uses the platform's established authentication and Dataverse security model instead of a separately authored API definition. A custom connector would only be justified for an unsupported proprietary endpoint or functionality that the standard connector does not expose and that cannot be addressed through supported Dataverse operations. It would be wasteful to recreate common table access. The Study Guide's cloud-flow section includes "evaluate and recommend connectors" and "configure cloud flow actions." The standard Dataverse connector directly satisfies the requirement, so the proposed situation does not demonstrate a need for a custom connector. The correct response is No.
Study Guide reference/topic: "Create cloud flows - Evaluate and recommend connectors." AB-410 Study Guide | Microsoft Learn technical reference
NEW QUESTION # 27
A company is designing an AI-enabled solution to help employees review and evaluate customer requests.
The company requires an AI summary to be generated at runtime by using instructions provided by the company, including tone, structure, and required data fields. The Prompt control will use these instructions on Power Apps forms across multiple tables.
You need to store the instructions.
Which component should you use?
Answer: D
Explanation:
To achieve a reusable, multi-table runtime AI summarization tool, you must use Custom AI Prompts configured via the AI Prompt Builder and stored in Microsoft Dataverse.
You should use AI Builder Prompt builder in the Microsoft Power Platform. It perfectly meets your requirements to create, store, and dynamically process instructions across multiple Power Apps tables and forms.
Prompt builder: Use this capability in the Power Apps Maker portal to draft, test, and save custom instructions for the AI. You can explicitly dictate the tone, structure, and required data fields within the prompt.
'Dynamic Values & Input Variables: Add dynamic input fields to your prompts so they ingest contextual data from different Dataverse tables and form controls.
Solution Lifecycle Management: The stored prompts are "solution-aware" components. They are saved directly in your environment and can be easily deployed and reused across different applications and tables.
Power Fx Integration: Trigger the AI summary at runtime by using Power Fx formulas to invoke your saved prompt. For example, on a button press, you would execute the formula:
Set(aiSummary, YourSavedPrompt.Predict(TextInput1.Text)).
Reference:
https://learn.microsoft.com/en-us/power-platform/release-plan/2025wave1/ai-builder/prompt-builder
NEW QUESTION # 28
An organization deploys an AI application handling customer information. The company must ensure transparency regarding AI-generated decisions and provide explanations to users. Which responsible AI principle applies?
Answer: B
Explanation:
Transparency is a responsible AI principle focused on explaining how AI systems operate and how decisions are produced. Users should understand when AI is involved and receive appropriate information about outcomes. Hardware optimization and compression improve technical performance but do not address ethical requirements or user understanding.
NEW QUESTION # 29
A company is creating a canvas app and a model-driven app to manage their customer accounts.
The canvas app requires a business rule to set the Business Type column to large if the customer size is greater than a specific currency value.
The model-driven app requires a business rule to recommend the account rating be re-evaluated when the account goes on credit hold for this app only.
You need to configure the scope for the business rules.
Which scope should you use? To answer, drag the appropriate scopes to the correct business rules. Each scope may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content. NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Business Type rule - Table scope; Account rating re-evaluation rule - Specific form scope
The Business Type rule should use Table scope because it must apply to the data regardless of which form or app is used, including the canvas app. Table-scoped business rules execute at the table level for supported operations and are not tied to one model-driven form. The account-rating recommendation is explicitly limited to one model-driven app form, so Specific form scope is the correct choice. This prevents the recommendation from appearing on other account forms that serve different processes. All forms would be broader than necessary because it applies the client-side rule to every main form for the table. The maker should confirm that the selected actions are supported at the chosen scope; not every form action is available at table scope. The original requirement to set Business Type based on customer size is data logic, whereas the rating recommendation is presentation guidance in a particular experience. The Study Guide explicitly lists "configure business rules." The verified mapping applies the narrowest effective scope: Table for reusable cross-app data behavior and Specific form for the app-limited recommendation.
Study Guide reference/topic: "Implement business and process logic - Configure business rules." AB-410 Study Guide | Microsoft Learn technical reference
NEW QUESTION # 30
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