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| Section | Weight | Objectives |
|---|---|---|
| Enhance solutions with AI and automation | 22% | - Use AI Hub models and pre-built capabilities
|
| Create a foundation for intelligent applications | 28% | - Implement responsible AI principles
|
| Build intelligent apps with Copilot and agents | 30% | - Create and manage agents with Copilot Studio
|
| Extend and secure intelligent solutions | 20% | - Secure access and data
|
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NEW QUESTION # 52
A company uses a model-driven app across multiple departments.
A public view intended only for managers currently exposes sensitive columns and filters to all users.
The view must meet the following requirements:
# Restrict access to the specific public view to managers.
# Display only context-relevant views for other users.
You need to configure view access.
What should you do?
Answer: D
Explanation:
The view should be assigned to the manager security role. The requirement is not to remove access to the underlying table; it is to limit one public view that exposes a sensitive arrangement of columns and filters.
Role-based public-view access allows the maker to associate the view with the manager role so it appears for managers but not for users whose roles are excluded. Table privileges are too broad because they govern operations on table rows and would affect every form, view, and app experience that uses the table. Removing the view from navigation does not prevent users from selecting it elsewhere in the model-driven app, and the Quick Find view controls search-result presentation rather than access to a particular public view. The solution should still confirm that sensitive columns have appropriate column-level security if their values must be protected independently of the view. For the stated visibility requirement, however, the targeted control is the view's role assignment. This maps directly to the AB-410 objective "configure access to forms and views for model-driven apps." Study Guide reference/topic: "Create model-driven apps - Configure access to forms and views." AB-410 Study Guide | Microsoft Learn technical reference
NEW QUESTION # 53
A company uses a Dataverse table to manage support cases.
You must provide employees with a summary of case information derived from multiple columns without requiring a manual review of the data.
The solution has the following requirements:
# Generate a case summary following the given instructions.
# Include the context of the current record in the generated output.
You need to configure the solution.
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 maker should define a prompt that references the support-case fields and create the destination column with the Prompt data type. The prompt contains the instructions for producing the case summary and declares the record inputs needed to ground that output. The prompt column then makes the generated summary available in the Dataverse/model-driven app context for the current row. A formula column performs deterministic Power Fx computation and cannot generate a natural-language summary from multiple fields. A business rule can set or validate values, but it does not invoke a generative model. The prompt should limit inputs to the approved columns, specify the required structure, and handle empty or contradictory case data so the generated content remains useful. Security on the source fields must still be respected, because an AI- generated summary must not become a route around restricted data. The AB-410 Study Guide lists "configure prompt columns" under Build data models and "add inputs to a prompt" under AI Hub. Options A and D supply the instruction definition and the Dataverse column behavior required for record-context generation.
Study Guide reference/topic: "Build data models - Configure prompt columns." AB-410 Study Guide | Microsoft Learn technical reference
NEW QUESTION # 54
An insurance company is implementing a customer service solution in Microsoft Dataverse to track interactions and manage issue resolution. The data model includes tables for customer information, support cases, and agents .
The data model includes the following requirements:
# Link each support case to a customer.
# Provide information on the children of customers.
# Record history of agents assigned to customers.
You need to configure table relationships.
Which relationships should you use? To answer, move the appropriate relationship to the correct requirement.
You may use each relationship once, more than once, or not at all. You may need to move the split bar between panes or scroll to view content. NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Support case to customer - One-to-many; Customer children - One-to-many; Agent assignment history - Connections
Each support case should reference one customer through a many-to-one lookup, which is configured from the customer perspective as a one-to-many relationship: one customer can have many cases. Customer children also require a self-referencing one-to-many relationship, allowing one customer row to be the parent of multiple child customer rows. Historical agent assignments are different. A conventional lookup retains only the current related row unless a separate history table is introduced. Dataverse Connections provide a flexible, role-based association between records and can retain multiple agent-to-customer links over time without redesigning the standard tables. A one-to-one relationship would prevent a customer from having multiple cases or children, and a many-to-many relationship is unnecessary where each case or child has one parent. The designer should define relationship roles and views so users can interpret the connection history consistently. The AB-410 Study Guide includes the exact objective "configure table relationships." The correct mapping uses one-to-many relationships for structured parent/child data and Connections for the flexible assignment-history requirement.
Study Guide reference/topic: "Build data models - Configure table relationships." AB-410 Study Guide | Microsoft Learn technical reference
NEW QUESTION # 55
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: A
Explanation:
Decreasing temperature makes the model's output more deterministic and less exploratory. For a support- knowledge prompt, that reduces variation and lowers the probability that the model invents unsupported wording when the same grounded information is supplied. Increasing temperature would encourage broader token selection and is counter to the requirement for reliable, repeatable answers. Content moderation level addresses detection or blocking of potentially harmful material; it is not the primary control for factual grounding or generation variance. Increasing moderation can be appropriate for safety policy, but it does not make a response more faithful to the internal knowledge source. The prompt should also contain precise instructions, approved grounding content, explicit handling for missing information, and a direction not to infer facts that are absent. Temperature is one control within that broader prompt-quality design. The Study Guide includes "customize prompt settings, including models" and "add knowledge to a prompt." Option C is the model-setting change that directly supports stable, conservative generation while retaining useful grounded responses.
Study Guide reference/topic: "Create prompts and models in AI Hub - Customize prompt settings." AB-410 Study Guide | Microsoft Learn technical reference
NEW QUESTION # 56
A company is building prompts in Microsoft Copilot Studio to support multiple customer service scenarios.
The company requires prompts to:
- Follow a consistent structure across use cases.
- Be reusable across multiple topics.
- Allow customization for different types of customer requests.
You need to build the prompts.
What should you do?
Answer: D
Explanation:
To best fulfill your requirements, you should create prompts by selecting templates from the prompt library and customizing them for each scenario.
The Microsoft Copilot Studio Prompt Library provides pre-built, standardized formats specifically designed to enforce a consistent structure. By taking a library-first approach and adding input/output parameters, you can build a modular system where a single base prompt is easily customized and reused across multiple topics.
Incorrect:
[Not A]
Configuring prompt model settings, on the other hand, only dictates the underlying LLM variant (e.g., GPT-4o) and generic runtime attributes, which does not solve for structural logic, reusability, or scenario customization.
Reference:
https://learn.microsoft.com/en-us/microsoft-copilot-studio/prompt-library
NEW QUESTION # 57
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