Advanced Power BI: Data Modeling, DAX Mastery & Enhanced Analytics

You already know how to build Power BI reports, but do you know why some dashboards feel instant, scalable, and insight-rich, while others struggle with slow performance and limited analytics?

The difference lies in advanced data modeling, DAX mastery, and analytical design—the skills that separate report builders from true Power BI experts.

This intensive 3-day advanced Power BI course is designed to help you cross that threshold. You’ll learn how to architect high-performance data models, write sophisticated DAX that adapts to business context, and apply advanced analytics that uncover patterns, not just numbers. Through hands-on labs and real-world scenarios, you’ll move beyond visuals and into decision-driving intelligence, building scalable, secure, and optimized Power BI solutions that stand up to real enterprise demands.

Learning Objectives

By the end of this course, participants will be able to:

• Design efficient data models using relationships, hierarchies, and normalization techniques.

• Master DAX for calculated columns, measures, and time intelligence.

• Apply advanced analytics techniques including forecasting, clustering, and decomposition.

• Optimize report performance and apply best practices for usability.

• Implement row-level security and governance strategies.

Prerequisites

Learners attending this course must have:

• Prior experience building Power BI reports.

• Familiarity with Power Query and basic DAX.

• Understanding of business data structures (tables, relationships).

Course Outline

Day 1: Advanced Data Modeling

Module 1: Power BI Architecture & Data Strategy

• Import vs. DirectQuery vs. Live Connection.

• Dataflows and shared datasets.

• Storage modes and performance impact.

• Lab: Connect to multiple sources and configure import vs. DirectQuery modes.

Module 2: Data Modeling Best Practices

• Star schema vs. snowflake schema.

• Relationships, cardinality, and cross-filtering.

• Hierarchies and normalization.

• Lab: Build a star schema model with proper relationships and hierarchies.

Module 3: Advanced Transformations with Power Query

• M language basics.

• Conditional columns and custom functions.

• Parameterized queries and query folding.

• Lab: Create a parameterized query with conditional logic and optimize for query folding.

Day 2: DAX Mastery

Module 4: DAX Fundamentals & Calculated Logic

• Calculated columns vs. measures.

• Filter context and row context.

• Common functions: CALCULATE, FILTER, ALL.

• Lab: Create calculated measures using CALCULATE and FILTER for dynamic KPIs.

Module 5: Time Intelligence in DAX

• Date tables and auto time intelligence.

• YTD, QTD, MTD, and rolling averages.

• Custom time periods and offsets.

• Lab: Build a time intelligence dashboard with YTD and rolling 12-month metrics.

Module 6: Advanced DAX Techniques

• Variables and nested logic.

• Iterator functions: SUMX, AVERAGEX, RANKX.

• Dynamic titles and slicer-driven calculations.

• Lab: Create dynamic visuals using RANKX and slicer-driven DAX expressions.

Day 3: Enhanced Analytics & Optimization

Module 7: Advanced Visualizations & Analytics

• Custom visuals and certified visuals.

• Forecasting, clustering, and decomposition tree.

• Drill-through and bookmarks.

• Lab: Build a report with drill-through, decomposition tree, and clustering insights.

Module 8: Performance Optimization

• DAX performance tuning.

• Query diagnostics and Performance Analyzer.

• Reducing report load time and memory usage.

• Lab: Use Performance Analyzer to identify bottlenecks and optimize DAX queries.

Module 9: Security, Publishing & Governance

• Row-level security (RLS).

• Workspace roles and deployment pipelines.

• Data governance and Power BI service settings.

• Lab: Implement RLS and publish a report with deployment pipeline stages.