PL-100T00: Microsoft Power Platform App Maker — Lesson 3: Automation, Analytics, and AI

Learning Objectives

• Create cloud flows with triggers, actions, conditions, approvals, and error handling
• Build Power BI insights and integrate them into the solution
• Use AI Builder or Copilot capabilities with human validation

Detailed Topics

• Create cloud flows with triggers: Create cloud flows with triggers, actions, conditions, approvals, and error handling
• Build Power BI insights and integrate them into the solution: Build Power BI insights and integrate them into the solution
• Use AI Builder or Copilot capabilities with human validation: Use AI Builder or Copilot capabilities with human validation

Guided Demonstration

1. Review the requirement, users, data, dependencies, permissions, risks, and expected result.
2. Demonstrate the relevant configuration, development, administration, collaboration, analysis, or automation workflow step by step.
3. Capture settings, outputs, logs, screenshots, calculations, test results, and other useful evidence.
4. Compare the observed result with acceptance criteria and explain any corrective action.

Hands-On Activity

Automate and analyze a business process.

• Document assumptions, prerequisites, and the planned sequence before starting.
• Complete the activity and preserve evidence of normal, boundary, and failure behavior.
• Record issues, corrective actions, reusable notes, and the next improvement priority.

Scenario Analysis

• Identify the business or technical decision that must be made.
• Compare valid implementation approaches and their trade-offs.
• Consider security, privacy, accessibility, performance, support, and operational impact.

Troubleshooting Focus

• Separate symptoms from causes and collect evidence before applying a fix.
• Check configuration, data, permissions, dependencies, capacity, connectivity, and recent changes.
• Validate rollback, recovery, ownership, user impact, and business continuity.

Validation Checklist

• The requirement, scope, inputs, and expected outcome are clear.
• The selected design or configuration is documented and follows approved standards.
• Normal, boundary, failure, security, accessibility, and operational conditions are reviewed.
• The result is supported by evidence and the next improvement is prioritized.

Lesson Outcome

Learners can explain and apply Automation, Analytics, and AI in a realistic scenario and validate the result with documented evidence.