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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Build intelligent apps with Copilot and agents | 30% | - Create and manage agents with Copilot Studio
|
| Topic 2: Create a foundation for intelligent applications | 28% | - Implement responsible AI principles
|
| Topic 3: Enhance solutions with AI and automation | 22% | - Build automation with Power Automate
|
| Topic 4: Extend and secure intelligent solutions | 20% | - Secure access and data
|
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NEW QUESTION # 117
A company wants to provide managers with visual insights into business performance data.
Managers require aggregated and visual representations of data directly within the app to be viewed in parallel with a list of rows. You need to configure the visual representation of data. What should you do?
Answer: A
Explanation:
A system chart is the native model-driven app visualization for aggregated Dataverse data and can be displayed alongside the rows in a selected view. The chart can group, count, sum, or otherwise aggregate supported columns and updates as the view or filters change. This directly meets the requirement for managers to compare a visual representation with the corresponding list of records inside the app. A Power BI semantic model can support richer analytics, but it adds an external analytical layer and is not necessary for the stated in-app chart requirement. App navigation determines where pages and tables appear, while general app settings do not create a visualization. The maker should create the chart for the appropriate table, choose the category and series fields, add the chart to the app, publish, and verify that managers have access to the underlying rows and columns. Microsoft Learn lists model-driven app charts and dashboards within the AB-
410 create-intelligent-applications domain.
Reference: https://learn.microsoft.com/en-us/power-apps/maker/model-driven-apps/create-edit- system-chart Study Guide alignment: Create intelligent applications.
NEW QUESTION # 118
You are configuring a dashboard in a model-driven app for sales managers. The dashboard displays opportunity pipeline data from the Opportunities table.
The company requires the following functionality:
# Show how each sales stage contributes to the total pipeline for each sales region.
# Ensure a newly created chart is available to users in the app.
# Use the My Open Opportunities dataset when the dashboard component loads.
# Prevent users from switching to a different chart at runtime.
You need to create and configure the chart and dashboard component.
How should you configure the requirements? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Regional contribution - Stacked column chart; Publish chart in app - Select the chart for the table in app designer; Initial dataset - Set the Default View; Prevent chart switching - Clear Display Chart Selection
A stacked column chart is appropriate because each regional column can display the sales-stage segments that compose the region's total pipeline, making both overall magnitude and stage contribution visible. A standard column chart would compare separate values but would not show composition in the same bar, while a pie chart does not compare multiple regional totals effectively. The chart must be selected for the Opportunities table in the app designer so it becomes part of the model-driven app package available to users. The dashboard component's Default View should be set to My Open Opportunities so that dataset loads initially.
To prevent runtime chart switching, Display Chart Selection must be cleared; otherwise users can choose another available chart. "Default Chart" determines which chart opens first but does not prevent selection of others. The maker should verify that the chosen view and chart are shared through the app and that users have privileges to the underlying opportunity records. The Study Guide explicitly covers "create and configure model-driven app charts and dashboards." These four settings govern visualization type, app inclusion, initial data context, and runtime choice independently.
Study Guide reference/topic: "Create model-driven apps - Create and configure charts and dashboards." AB-410 Study Guide | Microsoft Learn technical reference
NEW QUESTION # 119
A company develops an AI chatbot using Azure OpenAI. Security administrators require that customer data must not be used to train public foundation models. Which statement correctly describes Azure OpenAI data handling?
Answer: A
Explanation:
Azure OpenAI provides enterprise data protection where customer prompts, completions, and training data are not used to train public OpenAI models. Data isolation and security controls are key enterprise features. Organizations can build applications while maintaining control over their information. Public model improvement processes are separate from Azure OpenAI customer workloads.
NEW QUESTION # 120
A company uses a cloud flow to analyze incoming order form PDFs attached to emails.
The cloud flow must use an AI model to extract information from each order. The information must then be added to the enterprise resource planning (ERP) system.
You need to configure the flow.
Which two actions should you perform? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.
Answer: D,E
Explanation:
The two actions required to configure the flow for extracting information from order form PDFs are:
Add the Process documents action
Specify the model, document type, and document
Add the Process documents action: In Microsoft Power Automate AI Builder, the specific action designed to analyze and extract information from layout-heavy structures like PDFs, invoices, or order forms is called Process documents (historically named Extract information from documents).
Specify the model, document type, and document: When configuring the Process documents action, you must explicitly select your custom or prebuilt document processing model, define the document type (e.g., fixed-template or general document), and pass the file content parameter (the incoming email attachment document).
Reference:
https://learn.microsoft.com/en-us/ai-builder/prebuilt-entity-extraction-pwr-automate
NEW QUESTION # 121
Fabrikam Inc. develops Power Platform applications directly in its production environment. The company has no structured application lifecycle management (ALM) process, and solutions are not consistently used to package or deploy components.
The company has the following requirements:
- Separate environments must be used for development, testing, and production.
- Solutions must be segmented by functional areas.
- Managed solutions must be deployed to production.
- Changes must be validated before production deployment.
You need to meet the ALM requirements.
What should you do?
Answer: A
Explanation:
Multiple unmanaged solutions enable Fabrikam Inc. to organize Power Platform application components according to their functional responsibilities during development. Each solution can contain the Dataverse tables, Power Apps applications, Power Automate flows, and related components required by a particular business function. This structure supports modular development, controlled packaging, independent testing, and maintainable application lifecycle management. Development occurs in unmanaged solutions because makers must be able to modify components. Following testing and validation, these solutions can be exported as managed solutions for deployment to downstream environments, including production. A single unmanaged solution does not satisfy the requirement for functional segmentation. The Configuration Migration Tool transfers selected data rather than packaging application components. Microsoft recommends planning solution dependencies carefully and using managed solutions outside development environments to maintain reliable deployment governance.
Topic 1, Fabrikam Inc
Background
Fabrikam Inc. is an energy provider that operates wind and solar farms across multiple countries and regions.
The company uses Microsoft Power Platform to manage asset maintenance, technician workflows, and predictive analytics.
Field technicians use canvas apps on mobile devices to capture inspection and repair data. Operations managers use model-driven apps to monitor asset performance and maintenance history.
The company plans to enhance its platform by introducing AI-driven insights, improving reuse across applications, and establishing a formal application lifecycle management (ALM) strategy.
Current environment
Applications
Field technicians use an outdated mobile app to log maintenance activities and capture asset readings in SharePoint Online.
Operations managers use a model-driven app to review maintenance records and asset performance trends.
Development practices
Developers build and modify applications directly in the production environment.
There is NO structured ALM process.
Solutions are NOT consistently used to package or deploy application components.
Reusable components are inconsistently implemented across apps, leading to duplication.
AI integration
Fabrikam Inc. plans to actively explore generative AI usage as part of the next phase of work.
Business requirement
Application development
The outdated mobile app must be replaced with a new app that supports responsive design principles, provides full control over the UI, and allows technicians to take and upload photos directly from their mobile devices.
The new app for the field technicians requires the name of the technician to be persisted on the home screen only. In addition, work orders must be displayed within a gallery.
All new apps must connect to a scalable, cloud-based relational data store.
Apps must support efficient data entry for technicians in the field.
Reusable UI elements must be implemented to reduce duplication.
AI capabilities
The company requires a generative AI solution to manage customer complaint responses and create custom inspection reports that align to an existing template.
Customer complaint responses must be generated in applications and based on emails being sent to a mailbox.
Custom AI development must be minimized.
Generative AI reusability
Generative AI solutions must accept dynamic inputs to adapt to different scenarios.
Generative AI solutions must be reusable across different Power Platform services.
Extensibility
Custom UI form components must be reusable across applications.
Use of server-side custom code must be minimized where possible.
Technical requirements
Application lifecycle management (ALM)
Separate environments must be used for development, testing, and production.
Solutions must be used to package application components, segmented based on functional areas.
Managed solutions must be deployed to the production environment.
Validation must occur before deployment to production.
Data processing
Aggregated values across related rows must be displayed for reporting.
Calculations must update automatically as new data is entered. Calculation data must be limited to a maximum length of 10.
Issues
Duplicate logic exists across multiple canvas apps.
Developers frequently overwrite changes in production.
Generative AI solutions produce inconsistent outputs due to missing or inconsistent inputs.
Maintenance metrics are not consistently calculated across related rows.
NEW QUESTION # 122
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