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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Create a foundation for intelligent applications | 28% | - Design solutions using AI-enabled tools
|
| Topic 2: Enhance solutions with AI and automation | 22% | - Build automation with Power Automate
|
| Topic 3: Extend and secure intelligent solutions | 20% | - Deploy, monitor, and maintain solutions
|
| Topic 4: Build intelligent apps with Copilot and agents | 30% | - Integrate Copilot into canvas and model-driven apps
|
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NEW QUESTION # 18
A company creates an AI assistant that generates marketing content. Business users complain that responses vary significantly between identical requests. Which parameter should be adjusted?
Answer: D
Explanation:
Temperature controls randomness in generative AI output. Lower temperature values typically produce more consistent and predictable responses, while higher values increase creativity and variation. Storage, networking, and authentication settings do not influence model generation behavior. Adjusting temperature is a common method for controlling response consistency.
NEW QUESTION # 19
A company deploys a model-driven app to multiple departments.
The company requires the following app functionality:
# Enable users to open the app.
# Determine why users cannot access the app.
You need to configure app access.
Which actions should you perform? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Enable users to open the app - Share the app and assign appropriate security roles; Diagnose access - Run the App access checker
To enable users to open the model-driven app, the maker must share the app with the appropriate security roles and ensure users are assigned those roles. App visibility alone is not sufficient if the role lacks privileges to required Dataverse tables, but role-based sharing is the central app-access control. When a particular user still cannot open the app, the App access checker is the targeted diagnostic. It evaluates the user's app sharing, security roles, licensing, and related configuration and reports the access path or missing requirement. The solution checker reviews solution quality and component issues; it does not diagnose a user's effective app entitlement. Reviewing table permissions manually can be useful after a specific role problem is identified, but it is not the broad first diagnostic represented in the answer area. The checker should be run against the affected user identity and the exact app. This maps directly to the Study Guide objectives "configure access to model-driven apps" and "configure security." The two actions establish access and then provide a supported way to determine why effective access differs from the intended configuration.
Study Guide reference/topic: "Create model-driven apps - Configure access to model-driven apps." AB-410 Study Guide | Microsoft Learn technical reference
NEW QUESTION # 20
A company uses Power Apps.
Users must be able to view only the address1 columns in the Account table.
You need to ensure other address columns are not visible to users when creating views and filters.
What should you do?
Answer: B
Explanation:
Using column-level security to remove read access is the correct and most appropriate approach.
In Microsoft Dataverse, column-level security (CLS) applies a restrictive model organization-wide.
Once you enable column security on a column, all users automatically lose read, create, and write access to that column by default. Because the underlying data engine strictly blocks unauthorized access, these columns are automatically hidden from forms, system views, personal views, and filter dropdowns. This safely prevents users from adding restricted columns when they try to build their own custom views or query filters.
Reference:
https://learn.microsoft.com/en-us/power-apps/maker/data-platform/create-edit-field-solution-explorer
NEW QUESTION # 21
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:
The solution should use a prebuilt AI capability where it satisfies the complaint-processing requirement and create the generative prompt from blank for the organization-specific inspection report. Using a prebuilt model minimizes custom model development and training effort, which directly reflects the stated constraint.
A blank custom prompt gives the maker control over the inspection template, instructions, inputs, tone, and output format required by the business. Starting from a prompt template can accelerate common scenarios, but the case requires alignment to an existing custom inspection format; a blank prompt avoids carrying irrelevant template assumptions and permits deliberate grounding. Building a custom trained model would add data preparation, training, validation, and lifecycle overhead that the requirement seeks to minimize. The prompt should define required inputs explicitly and be tested with representative data to prevent the inconsistent output problem identified in the case. The Study Guide covers "build prompts from templates or from blank,"
"add inputs to a prompt," and consumption of AI capabilities in apps and flows. Options A and C provide the lowest-custom-development design that still supports the specific generative output.
Study Guide reference/topic: "Create prompts and models in AI Hub - Build prompts and consume AI capabilities." AB-410 Study Guide | Microsoft Learn technical reference
NEW QUESTION # 22
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.
(Choose three.)
NOTE: Each correct selection is worth one point.
Answer: B,D,E
Explanation:
To automate this customer feedback workflow, you must implement the following three components:
[A]
AI Builder (Sentiment Analysis Model)
Purpose: Autonomously analyzes customer feedback.
Function: Evaluates text natively within the Power Platform.
Action: Classifies feedback sentiment as positive, negative, or neutral without manual coding.
[B]
Power Automate (Cloud Flows)
Purpose: Orchestrates the entire automated workflow.
Function: Triggers when new feedback arrives (e.g., via email, forms, or social media).
Action: Passes text to AI, routes data to storage, and executes conditional logic for escalations.
[E]
Microsoft Dataverse
Purpose: Stores results for reporting and triggers downstream actions.
Function: Acts as the secure, relational data platform for the project.
Action: Holds the feedback text, sentiment scores, and historical data for Power BI reporting.
Reference:
https://learn.microsoft.com/en-us/ai-builder/flow-sentiment-analysis
NEW QUESTION # 23
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