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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Enhance solutions with AI and automation | 22% | - Build automation with Power Automate
|
| Topic 2: Create a foundation for intelligent applications | 28% | - Design solutions using AI-enabled tools
|
| Topic 3: Build intelligent apps with Copilot and agents | 30% | - Create and manage agents with Copilot Studio
|
| Topic 4: Extend and secure intelligent solutions | 20% | - Secure access and data
|
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NEW QUESTION # 83
A company is building a canvas app that spans multiple screens.
The app must store selected values across screens and hold tabular data during a session.
You need to manage application state.
Which two components should you use? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.
Answer: A,B
Explanation:
Use the following data storage and state management tools:
For Tabular Data: Use Collections. They hold rows and columns of data, persist across multiple screens, and are perfect for storing temporary data during a session before saving them permanently. You can create and populate one using the ClearCollect() function.
For Selected Values Across Screens: Use Global Variables or pass parameters directly in your Navigate() function. Use Set() for app-wide values, like an item ID or the current user.
Incorrect:
[Not B]
Context variables are tied to a single screen and are primarily meant for simple text, numbers, or toggling pop-ups. They cannot hold whole tables.
Reference:
https://dev.to/mattbuildsapps/power-apps-variables-explained-global-vs-context-vs-collections-4l9n
NEW QUESTION # 84
A company wants an AI system to analyze customer reviews and determine whether opinions are positive, negative, or neutral. Which Azure AI capability is most appropriate?
Answer: A
Explanation:
Sentiment analysis is a natural language processing capability used to determine emotional tone within text. It can classify opinions and provide confidence scores. Object detection analyzes images, speech synthesis generates audio, and document conversion changes formats. Review analysis is a common business scenario for sentiment analysis.
NEW QUESTION # 85
You need to configure the generative AI reusability requirements.
What should you do?
Answer: C
Explanation:
Calling the prompt from a Power Automate cloud flow provides a reusable service-level entry point that can be invoked by different Power Platform experiences. The flow can accept parameters from each caller, pass those values into the prompt, and then route the generated result to an app, Dataverse, email, or another process. This addresses reuse more effectively than binding the prompt directly to one canvas app. An input variable is necessary for dynamic data, but by itself it does not establish cross-service orchestration; the flow exposes and manages those inputs for multiple callers. Returning JSON can standardize output handling but does not make the prompt reusable by itself. Direct canvas-app invocation is valid for an app-only requirement, not for the stated need to span Power Platform services. The flow should define explicit input types and validate required values so the case's inconsistent-input problem is not repeated. The AB-410 Study Guide lists both "add inputs to a prompt" and "consume a prompt in cloud flows." Option B provides the reusable execution layer while allowing dynamic values to be supplied at runtime.
Study Guide reference/topic: "Create prompts and models in AI Hub - Consume a prompt in cloud flows." AB-410 Study Guide | Microsoft Learn technical reference
NEW QUESTION # 86
A company plans to use Microsoft Dataverse to manage sales opportunities. Records will contain confidential financial data that should only be accessible to specific groups of employees.
You have the following requirements:
# Sales representatives must only view and update records they create.
# Sales managers must have visibility into all opportunities within their organization.
You need to configure security.
Which configuration should you use? To answer, select the appropriate options in the answer area. NOTE:
Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Sales representatives - User-level access; Sales managers - Organization-level access
User-level access is the correct depth for sales representatives because it limits table privileges to records they own or create. The security role can grant Create, Read, Write, and any required related privileges at the User scope, ensuring that one representative cannot automatically open another representative's opportunity. Sales managers require Organization-level access because the requirement explicitly states that they must see all opportunities in the organization. Organization depth applies the permitted operation across business units, unlike Business Unit or Parent: Child Business Unit depth, which would restrict visibility to part of the hierarchy. The actual role should grant only the operations managers need; organization-wide Read does not necessarily require organization-wide Delete. Field-level security should be added separately if particular financial columns require tighter control than the row itself. Sharing and team ownership can address approved exceptions without broadening the base role. The Study Guide's exact data-model objective is
"configure security." This mapping implements least privilege at two different record-access depths while preserving the required managerial visibility.
Study Guide reference/topic: "Build data models - Configure security." AB-410 Study Guide | Microsoft Learn technical reference
NEW QUESTION # 87
A developer needs an AI model to classify incoming emails into categories such as billing, technical support, and complaints. The categories are predefined and training examples are available. Which machine learning approach is appropriate?
Answer: C
Explanation:
Classification models assign data into predefined categories based on learned patterns. Email routing scenarios commonly use supervised classification because labeled examples exist.
Clustering is used when categories are unknown, regression predicts numerical values, and reinforcement learning focuses on decision-making through rewards rather than direct category assignment.
NEW QUESTION # 88
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