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| Section | Weight | Objectives |
|---|---|---|
| Create a foundation for intelligent applications | 28% | - Implement responsible AI principles
|
| Enhance solutions with AI and automation | 22% | - Use AI Hub models and pre-built capabilities
|
| Extend and secure intelligent solutions | 20% | - Deploy, monitor, and maintain solutions
|
| Build intelligent apps with Copilot and agents | 30% | - Create and manage agents with Copilot Studio
|
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NEW QUESTION # 37
A company builds a canvas app to display and manipulate large datasets across multiple screens.
Users report the app takes a long time to load data when opened.
You need to optimize performance when the app is started.
What are three actions you can perform? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.
Answer: B,D,E
Explanation:
To optimize the startup performance of a Canvas app handling large datasets, you must focus on reducing the initial data payload and parallelizing operations.Here are three high-impact steps you can take:
[B] Remove data retrieval calls from App.OnStart:
Heavy data loading in App.OnStart blocks the app from rendering, forcing users to stare at a loading screen. Moving these calls to the OnVisible property of the first screen allows the UI to load immediately while data fetches in the background.
[D] Enable Concurrent Data Loading
By default, Power Apps loads data sources sequentially. You can use the Concurrent function in the App.OnStart or App.StartScreen property to load multiple collections or data sources at the exact same time. This dramatically reduces initial wait times.
[E] Use the ClearCollect() function to cache data: Storing large, frequently accessed datasets locally in a collection prevents the app from making repeated, slow network calls to the data source across multiple screens.
Reference:
https://learn.microsoft.com/en-us/power-apps/guidance/coding-guidelines/code-optimization
NEW QUESTION # 38
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: C,D
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 # 39
You need to assign 10 percent of the Qualification rows to the QV queue through table configuration by using a Power Automate flow.
What should you do?
Answer: C
Explanation:
A rollup column on Service Request can count the directly related Qualification rows because Dataverse rollups support the COUNT aggregate over a 1:N relationship. The Power Automate flow can use that total as the upper bound for a generated random number and select a Qualification when the generated value falls within the lowest 10 percent of the range. This provides sampling within each service request instead of selecting every tenth record across the entire Qualification table. A formula column cannot aggregate an arbitrary set of related child rows, which eliminates option B. An autonumber on Qualification could identify every tenth row globally, but it would not reliably sample 10 percent of the qualifications belonging to each service request and gaps or prefixes can distort the method. An autonumber on Service Request is even less relevant because selection occurs at the Qualification level. Rollup values are calculated asynchronously and can be stale, so the implementation should explicitly recalculate or retrieve the current related-row count before sampling when exactness is required. Under the available choices, option C best matches the relational requirement.
Reference: https://learn.microsoft.com/en-us/power-apps/maker/data-platform/define-rollup-fields Study Guide alignment: Build business application logic and automation.
NEW QUESTION # 40
A company uses Dataverse to manage customer accounts and related transaction records.
The company requires the following functionality:
Reference a single related record without performing any aggregations.
Store the relationship as part of the table definition, so the platform automatically maintains the link between records.
You need to configure a column.
Which type of column should you configure?
Answer: D
Explanation:
A Lookup column is designed to reference one row in another Dataverse table. The selected related row's identifier is stored as part of the relationship, and Dataverse maintains the association so forms, views, queries, and security behaviors can work with it consistently. The requirement explicitly excludes aggregation, which rules out a Rollup column; rollups calculate values such as sum, count, minimum, maximum, or average over related rows. A Calculated column evaluates an expression from other values, while a Formula column uses Power Fx to derive a result. Neither is the correct structural mechanism for selecting and maintaining a single related account or transaction row. The lookup's relationship should be configured with the appropriate required level, cascade behavior, and delete rule so it matches the record lifecycle. This is not merely a display field: it is a schema-level relationship component. The AB-410 Study Guide lists "create and modify columns" and "configure table relationships" under Build data models. A Lookup column is therefore the only option that natively represents the required one-record association.
Study Guide reference/topic: "Build data models - Create and modify columns." AB-410 Study Guide | Microsoft Learn technical reference
NEW QUESTION # 41
A company uses a prompt to generate responses based on internal support knowledge.
The company requires the prompt to minimize generation of unsupported and incorrect information while ensuring responses remain useful.
You need to tune the prompt model settings.
How should you configure the model settings?
Answer: B
Explanation:
To minimize unsupported information and ensure factual accuracy, you should decrease the temperature setting to a low value, typically between 0.0 and 0.3. Lowering the temperature forces the model to prioritize the most probable words, making the responses conservative, deterministic, and tightly aligned with your internal support knowledge base.
Reference:
https://learn.microsoft.com/en-us/microsoft-copilot-studio/guidance/optimize-prompts-topic-configuration
NEW QUESTION # 42
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