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| Section | Weight | Objectives |
|---|---|---|
| Create a foundation for intelligent applications | 25-30% | - Build data models in Dataverse
|
| Create intelligent applications | 25-30% | - Create canvas apps
|
| Build business application logic and automation | 40-45% | - Business logic
|
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NEW QUESTION # 42
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 # 43
A company wants to build a generative AI assistant that answers employee questions using internal policies stored in SharePoint. The assistant must provide responses based only on approved company documents. Which architecture pattern should be implemented?
Answer: A
Explanation:
Retrieval-Augmented Generation (RAG) combines a language model with external knowledge retrieval. The system searches approved documents and provides relevant context to the model before generating answers. Fine-tuning changes model behavior but does not guarantee access to current information. RAG is preferred for enterprise assistants requiring grounded responses from organizational data sources.
NEW QUESTION # 44
An organization wants to deploy an AI application that identifies defective products from manufacturing camera images. The company has thousands of labeled images and requires a customized model with continuous retraining capabilities. Which Azure service should be used?
Answer: B
Explanation:
Azure Machine Learning provides tools for developing, training, deploying, and managing custom machine learning models. Because the organization has labeled images and requires continuous retraining, a custom ML workflow is appropriate. Azure AI Vision offers prebuilt capabilities but is less suitable when specialized industrial image recognition models must be trained and optimized.
NEW QUESTION # 45
You create a parent entity and a child entity. The parent entity has a 1:N relationship with the child entity.
You need to ensure that when the owner changes on the parent record that all child records are assigned to the new owner.
You need to configure the relationship behavior type.
What should you use?
Answer: A
Explanation:
To automatically assign all child records to a new owner when the parent record's owner changes, you must use a Parental relationship behavior type, or a Configurable Cascading relationship behavior type with the Assign action set to Cascade All.
Reference:
https://learn.microsoft.com/en-us/dynamics365/customerengagement/on-premises/customize/create-and-edit-1n-relationships
NEW QUESTION # 46
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:
Correct:
* A cloud flow must integrate with an internal web service that is used across multiple flows and requires reusable actions.
This scenario requires a custom connector. Because it is a proprietary or internal service, Microsoft does not provide a pre-built native bridge. Building a Microsoft Custom Connector wraps the web service's REST/SOAP API into a reusable tool, eliminating the need to repeatedly configure HTTP headers and endpoints across separate flows.
Incorrect:
* A cloud flow must call a REST API by using a one-time HTTP action without reuse across flows.
A custom connector is not necessary here. For single-use or non-reusable integrations, using a generic built-in HTTP action step is the most efficient and fastest choice.
* A cloud flow must retrieve data from Microsoft Dataverse.
Power Automate includes a native, out-of-the-box Microsoft Dataverse connector. There is no need to develop a custom connector for default Power Platform data storage.
* A cloud flow must retrieve data from SharePoint Online lists.
SharePoint Online is fully supported by native Microsoft 365 integrations. You should use the pre- built SharePoint connector instead of creating a custom wrapper.
Reference:
https://alphavima.com/blog/power-apps-custom-connector-rest-api/
NEW QUESTION # 47
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