Skills at a glance

• Design automations (25–30%)

• Develop automations (45–50%)

• Deploy and manage automations (20–25%)

Design automations (25–30%)

Design automations using Power Automate features and capabilities

• Leverage the Power Automate ecosystem

• Differentiate between cloud flows and desktop flows

• Design automations using desktop flows and cloud flows

• Differentiate trigger types for cloud flows

• Differentiate options for interacting with target applications and browsers

• Differentiate the different methods for running a desktop flow

• Assess the ability to run cloud and desktop flows concurrently

• Recommend running desktop flows attended versus unattended

• Differentiate HTTP actions in cloud and desktop flows

• Assess if work queues are applicable for the automation

• Design custom actions

Design automations using other Microsoft Power Platform features and capabilities

• Design automations that include canvas and model-driven apps

• Design automations using connectors, custom connectors, connection references, and connections for cloud flows

• Design automations that include Microsoft Dataverse

Design automations that analyze and enhance data and documents

• Differentiate Microsoft AI options for processing documents in desktop and cloud flows

• Differentiate Microsoft AI options for processing data in desktop and cloud flows

• Recommend optical character recognition (OCR) capabilities in desktop flows

• Recommend Document Automation Toolkit for use in automation design

Design automations using scripting languages in desktop flows

• Design automations using scripting languages including PowerShell and Visual Basic Script (VBScript)

• Recommend automation use cases that use JavaScript

• Design an automation that uses the document object model (DOM)

Develop automations (45–50%)

Develop cloud flows

• Develop a cloud flow that calls a desktop flow

• Develop and use child cloud flows including passing and returning data

• Perform actions in cloud flows by calling external APIs

• Implement trigger conditions and concurrency in cloud flows

• Implement timeout and retry policies in cloud flows

• Implement data objects and data operations in cloud flows

• Perform text parsing including JSON, XML, and CSV in cloud flows

Develop desktop flows

• Implement UI options

• Implement datatables, lists, and custom objects in desktop flows

• Implement subflows in desktop flows

• Perform actions in desktop flows by calling external APIs

• Implement timeout and retry in desktop flows

• Implement data objects and data operations in desktop flows

• Perform text parsing including JSON, XML, and CSV in desktop flows

• Implement custom actions in desktop flows

Implement logic in cloud and desktop flows

• Implement flow control in cloud and desktop flows including loops

• Implement expressions in cloud flows

• Implement variable actions for cloud and desktop flows

• Implement secure input and output data in actions in cloud flows

• Implement secure variables in desktop flows

• Implement priority for desktop flows in a queue

• Implement exception handling blocks in cloud and desktop flows to handle system exceptions

• Implement error handling routines in cloud and desktop flows to handle business exceptions

• Implement work queues in cloud and desktop flows

Build custom connectors and implement connector configurations

• Build a custom connector

• Implement authentication for custom connectors

• Implement custom connector policy templates

• Develop code in a custom connector

Perform automation infrastructure management

• Recommend credential management practices

• Utilize on-premises data gateway to connect resources from cloud flows

• Build components in Microsoft Dataverse solutions

Test automations and finalize development efforts

• Test a cloud flow

• Test a desktop flow

• Utilize environment variables and configuration files to manage configurations

• Utilize debugging features in cloud and desktop flows

Deploy and manage automations (20–25%)

Perform target environment preparation

• Implement Microsoft Power Platform application lifecycle management (ALM)

• Differentiate credentials used for different environments

• Recommend how to deploy solution components to other environments

• Build virtual desktop environments for unattended desktop flow execution

Assess data loss prevention (DLP) policies for RPA execution

• Assess Microsoft Power Platform DLP policies

• Assess how DLP policies impact actions in cloud and desktop flows

• Assess how DLP policies apply to custom connectors

Implement access to RPA components

• Perform sharing of cloud and desktop flows

• Perform sharing of machines and machine groups

• Recommend security roles required to run and monitor cloud and desktop flows

• Implement service accounts and service principals

Implement machine groups and queues required for desktop flow automations

• Assess machine and machine group requirements

• Perform machine registration management

• Perform machine group management

• Implement load balancing of desktop flows by using machine groups and queues

• Perform operations on the run queue to manage desktop flows

• Analyze cloud and desktop flow run history from the Power Automate portal