Microsoft Excel BI — Lesson 3: Power Pivot, Relationships and DAX

Lesson Overview

This 4 hours lesson develops practical knowledge of Power Pivot, Relationships and DAX within Microsoft Excel BI.

The lesson connects concepts to implementation decisions, evidence collection, troubleshooting, quality controls, and measurable validation.

Create normalized data models with tables, relationships, cardinality, hierarchies, calendars, and calculated columns
Use DAX measures for totals, ratios, time intelligence, context, variance, and performance indicators
Validate power pivot, relationships and dax decisions with documented requirements, test evidence, risk controls, and measurable acceptance criteria

Create normalized data models with tables: Create normalized data models with tables, relationships, cardinality, hierarchies, calendars, and calculated columns
Use DAX measures for totals: Use DAX measures for totals, ratios, time intelligence, context, variance, and performance indicators
Validate power pivot: Validate power pivot, relationships and dax decisions with documented requirements, test evidence, risk controls, and measurable acceptance criteria

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

Develop a controlled Excel data model and measure set.

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.

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.

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.

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.

Learners can explain and apply Power Pivot, Relationships and DAX in a realistic scenario and validate the result with documented evidence.