Microsoft Power Automate RPA Developer Practice Tests and PDFs

To implement security to resolve the invoice data issue, you need to perform three actions: In Microsoft Power Platform admin center, navigate to the Security roles section. This is where you can manage the security roles for your environment and assign them to users or teams. Select the Finance role, select Custom Entities and navigate to the table. This is where you can configure the access level for each entity in your environment based on your security role. Clear the Create and Delete permissions. Set the Read permission and Write permission values to Business unit. This will restrict users with this role from creating or deleting records in this table, but allow them to read or write records within their business unit.

To resolve the fulfillment status flow issue, you need to perform three actions: Ensure that all users are signed out from the target machine. This will prevent any interference or interruption from other users who might be logged in to the same machine where the desktop flow is running1. Use different local Windows accounts for all machines. This will ensure that each machine has a unique identity and credentials for running desktop flows1. Ensure that the flow is not using elevated privileges. This will avoid any security risks or errors that might occur when running desktop flows with administrator rights1.

According to the scenario, the SMSApp data entry issue occurred after a DLP policy change that excluded the development environment from its scope. This means that any desktop flow that uses connectors in the development environment will be blocked by the DLP policy1. Therefore, the root cause of the issue is option D.

To configure a flow for processing invoices that arrive in an email, you need to use three elements: document type, AI model, and form type. Document type specifies what kind of document you want to process, such as invoices, receipts, or business cards. AI model determines how the document data will be extracted and analyzed, such as using a prebuilt model or a custom model. Form type defines how the extracted data will be mapped to a table in Dataverse, such as using a standard form or a custom form.