Advanced Data Modeling and Shaping with Power BI — Lesson 2: Semantic Model Architecture

Learning Objectives

• Define grain and create robust fact and dimension tables
• Configure active, inactive, role-playing, and many-to-many relationships
• Use date tables, hierarchies, sort columns, and model metadata

Detailed Topics

• Define grain and create robust fact and dimension tables: Define grain and create robust fact and dimension tables
• Configure active: Configure active, inactive, role-playing, and many-to-many relationships
• Use date tables: Use date tables, hierarchies, sort columns, and model metadata

Guided Demonstration

1. Review the requirement, users, data, dependencies, permissions, risks, and expected result.
2. Demonstrate the relevant configuration, application, automation, analysis, or administration 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

Design a semantic model for a complex analytical scenario.

• 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 Semantic Model Architecture in a realistic scenario and validate the result with documented evidence.