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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Create a foundation for intelligent applications | 25-30% | - Design Microsoft Power Platform solutions using AI-enabled tools
|
| Topic 2: Build business application logic and automation | 40-45% | - Create cloud flows
|
| Topic 3: Create intelligent applications | 25-30% | - Create canvas apps
|
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NEW QUESTION # 157
You need to set up the capability to view the change history for the food type and amount. What should you set up? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Feature: Audit changes to its data. Table: Resident.
Food type and amount are columns on the Resident table, so Dataverse auditing must be enabled for that table and for the two relevant columns. The Audit changes to its data setting records create, update, and delete events and captures the user and time associated with audited changes. This directly supports the requirement to identify who changed the values during the preceding three months. The audit-retention policy should therefore retain records for at least that period. The Feeding table is not the correct target because the scenario explicitly states that food type and amount are stored on each Resident row. A timeline displays activities and notes but does not automatically provide field-level before-and-after history. Audit user access records access events and is not a substitute for auditing data changes. Environment-level auditing must also be enabled before table and column auditing produces history. Microsoft documents that audited changes can be retrieved with Changed By and Created On information, allowing authorized staff to determine who made each modification and when it occurred.
Reference: https://learn.microsoft.com/en-us/power-apps/developer/data-platform/auditing/retrieve-audit-data Study Guide alignment: Create a foundation for intelligent applications.
NEW QUESTION # 158
A company wants to reduce the cost of calling a large language model while maintaining acceptable response quality for simple requests. Which strategy should be considered?
Answer: D
Explanation:
Using smaller or specialized models for simpler tasks can reduce inference costs while maintaining acceptable performance. Large models should be reserved for complex reasoning scenarios. Increasing token usage and duplicate requests increase expenses. Effective AI architecture uses workload classification and selects appropriate models based on business requirements.
NEW QUESTION # 159
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:
Disabling the Searchable property for the unwanted address columns removes them from maker-facing query and view design experiences where searchable columns are offered for views, charts, and Advanced Find- style filtering. That directly addresses the requirement that users should not be able to select those columns while creating views and filters. Column-level security is not a metadata-hiding feature: removing Read access protects values at runtime but does not reliably remove the column definition from customization or query interfaces. A business rule can change controls on forms, but it does not govern which columns are available to a view designer. Deleting standard address columns is destructive, can break dependencies, and is unnecessary. The original answer A therefore over-applies data security to what is fundamentally a discoverability/configuration requirement; D is the verified answer. If the values themselves are sensitive, column security may be implemented in addition, but that is a separate requirement. This decision aligns with the AB-410 objectives "create and modify columns" and "configure public views," particularly the use of column metadata to shape view and filter authoring.
Study Guide reference/topic: "Build data models - Create and modify columns; Configure public views." AB-410 Study Guide | Microsoft Learn technical reference
NEW QUESTION # 160
A company wants to monitor an AI application's performance after deployment. The team needs information about response quality, latency, failures, and user interactions. Which practice should be implemented?
Answer: D
Explanation:
Monitoring and telemetry provide visibility into AI application behavior after deployment. Important metrics include latency, errors, user feedback, and response quality. Production AI systems require continuous evaluation because data patterns and user expectations change over time.
Model weights alone cannot reveal operational issues or application performance problems.
NEW QUESTION # 161
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 integrate with an internal web service that is used across multiple flows and requires reusable actions .
Does the solution meet the goal?
Answer: B
Explanation:
This is an appropriate custom connector use case. The internal web service is a proprietary API and its actions must be reused across multiple flows. A custom connector centralizes the service's host, authentication, paths, parameters, request bodies, and response schemas and exposes each operation as a named Power Automate action. Makers can then use a consistent contract rather than rebuilding raw HTTP requests with different headers or payloads in every flow. The connector can be defined from an OpenAPI document or configured manually and should be packaged in a solution with connection references. If the service is reachable only on a private network, an on-premises data gateway or approved network architecture may also be required. Data loss prevention policies should classify the connector appropriately, and changes to the API should be versioned and regression-tested against dependent flows. The Study Guide explicitly measures the ability to
"evaluate and recommend connectors." The combination of a nonstandard internal service and reusable operations is precisely the situation in which the managed abstraction of a custom connector is justified. The answer is Yes.
Study Guide reference/topic: "Create cloud flows - Evaluate and recommend connectors." AB-410 Study Guide | Microsoft Learn technical reference
NEW QUESTION # 162
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