Duration 3 days – 21 hrs

 

Overview

 

This advanced Power BI training is designed for professionals who want to go beyond dashboards and build enterprise-ready analytics solutions using advanced data modeling and DAX (Data Analysis Expressions). Participants will learn how to design efficient models, develop accurate and optimized DAX measures, apply time intelligence and advanced filtering techniques, and use analytical patterns for KPI tracking, forecasting-ready models, and performance improvement.

 

By the end of this course, participants will be able to create scalable and high-performing Power BI reports using industry best practices in data modeling, advanced DAX calculations, and analytics design.

 

Objectives

 

• Design efficient star-schema models and optimize relationships for analytics performance
• Build advanced DAX measures using key functions, context rules, and calculation patterns
• Apply time intelligence (YTD/MTD/QTD, rolling periods, comparisons, and trends)
• Develop complex KPIs using CALCULATE, FILTER, ALL, ALLSELECTED, VALUES and variables
• Implement advanced analytics patterns like segmentation, ranking, Pareto, cohorts, and dynamic measures
• Optimize report performance using best practices in modeling and DAX tuning
• Create scalable and reusable reporting designs using measure tables, calculation groups (optional), and documentation standards

 

Target Audience

 

• Power BI Developers / BI Analysts
• Data Analysts / Reporting Analysts
• Finance Analysts & FP&A Professionals using Power BI
• Business Analysts handling data models and KPIs
• Data & Analytics Teams building enterprise dashboards
• Professionals transitioning from intermediate to advanced Power BI development

 

Prerequisites 

• Basic to Intermediate Power BI skills (creating visuals, basic measures)

• Familiarity with importing data using Power Query

• Understanding of basic relationships and tables

• Basic knowledge of Excel formulas is helpful

• Recommended: Completion of a Power BI Fundamentals / Intermediate course

 

Course Outline 

 

Module 1: Advanced Power BI Data Modeling

 

• Review: Power BI architecture (Data Model + DAX + Visuals)
• Designing an analytics-ready model
• Star schema vs snowflake schema (practical decision guide)
• Relationship behaviors: single vs both direction
• Many-to-many relationships (use cases and risks)
• Bridge tables and role-playing dimensions (Date table techniques)
• Modeling best practices for enterprise reporting

Hands-on Exercise: Model redesign for performance and accuracy

 

Module 2: DAX Foundations for Advanced Analytics

 

• DAX measure vs calculated column (proper use cases)
• DAX evaluation contexts:
  • Row context
  • Filter context
  • Context transition
• Understanding iterators: SUMX, AVERAGEX, RANKX
• Using VAR (variables) for clean and optimized DAX
• Debugging incorrect results (common mistakes)
• Hands-on Exercise: Convert complex formulas into clean VAR-based measures

Module 3: Mastering CALCULATE and Filter Manipulation

 

• Deep dive into CALCULATE() behavior
• Filter functions and patterns:
  • FILTER()
  • ALL(), ALLEXCEPT()
  • ALLSELECTED()
  • VALUES(), DISTINCT()
  • REMOVEFILTERS(), KEEPFILTERS()
• Creating responsive measures with slicers
• Common advanced patterns:
  • % of total
  • Weighted averages
  • Contribution analysis

• Hands-on Exercise: Build dynamic % contribution and market share KPIs

 

Module 4: Advanced Time Intelligence

 

• Building a proper Date table (best practice)
• Core time intelligence patterns:
  • MTD, QTD, YTD
  • Prior period comparison
  • YoY growth measures
• Rolling time patterns:
  • Rolling 7/30/90 days
  • Trailing 12 months
• Handling custom fiscal calendars
• Time intelligence without built-in functions (custom logic)

• Hands-on Exercise: Create a full KPI pack (YTD, LY, YoY%, Rolling 12 Months)

 

Module 5: Advanced Analytical Measure Patterns

 

• Ranking & sorting:
  • Top N and Bottom N analysis
  • Dynamic ranking with slicers
• Pareto / 80-20 rule analysis
• Segmentation & grouping:
  • Customer tiering
  • Product classification (A/B/C)
• Cohort analysis (intro pattern)
• KPI status & thresholds (RAG indicators)
• Hands-on Exercise: Build a Pareto analysis dashboard using DAX measures

 

Module 6: Advanced Visual Analytics Techniques

 

• Dynamic titles and labels using DAX
• Conditional formatting (rules + measure-driven)
• Drillthrough and report navigation design patterns
• Field parameters (dynamic dimension switching)
• What-if parameters and scenario modeling
• Smart tooltips for insight drilling
• Hands-on Exercise: Create a dynamic executive dashboard (switch metrics + drill insight)

 

Module 7: Performance Optimization & Best Practices

 

• Common causes of slow performance:
  • Model design issues
  • Overuse of calculated columns
  • Inefficient DAX patterns
• DAX optimization strategies:
  • Reduce iterator dependency where possible
  • Replace heavy filters with simpler logic
  • Use measures instead of columns when appropriate
• Working with large datasets (practical guidance)
• Best practices for:
  • Measure naming conventions
  • Measure tables
  • Documentation standards
  • Version control practices (basic)

• Hands-on Exercise: Optimize slow measures and improve report responsiveness

 

Module 8: Capstone Workshop (Applied DAX Mastery)

 

• Participants will build an advanced Power BI report using:

• Proper modeling structure
• Advanced DAX KPI pack
• Time intelligence comparisons
• Ranking + Pareto analysis
• Interactive analytics dashboard

• Output: “Advanced Analytics Power BI Report Pack”