Design better Power BI models with star schemas. Justin Vogel explains facts, dimensions, grain, and relationships, plus practical patterns and pitfalls so reports stay fast, simple, and easy to use.
In Mastering the Star Schema, Justin Vogel walks you through how to design clean, intuitive data models that make reporting easier instead of harder. You’ll learn the core concepts of star schema ,design facts vs. dimensions, grain, surrogate keys, and relationships and why this structure is so widely used in analytics and Power BI. Justin shows how a good star schema simplifies DAX, improves performance, and helps report consumers slice and drill without confusion.
From there, you’ll see how to apply these ideas in practical scenarios. You’ll walk through modeling common business processes, handling slowly changing dimensions, dealing with role-playing dates, and avoiding common traps like snowflaking and over-normalization. Along the way, Justin shares naming, documentation, and validation tips so your models stay understandable and maintainable as they grow. By the end, you’ll know how to design star schemas that are robust, performant, and ready for self-service BI.
Course Outline ( Free Preview)
Module 01 - Agenda
Kick off the course with a clear roadmap of what you’ll learn and why it matters. Justin outlines the major modeling concepts you’ll cover from core star schema foundations to advanced table patterns and how each module builds toward designing cleaner, faster, more maintainable data models. This is your quick orientation so you know what to focus on as the course progresses.
Module 02 - Introduction
Justin sets the stage by explaining what a star schema is and why it’s the go-to structure for analytics and Power BI. You’ll get a high-level understanding of how star schemas make reporting easier, reduce complexity, and improve performance. This module also introduces the common modeling terms you’ll hear throughout the course so you’re never lost in jargon.
Module 03 - Dimensions & Facts: Star Schema Foundations17 min.
This is where the model starts to click. You’ll learn the essential difference between fact tables, things you measure, and dimension tables, things you slice by, plus why “grain” is one of the most important decisions you can make. Justin shows how these pieces fit together into a star schema and what a strong foundation looks like before you start building anything advanced.
Module 04 - Fact Table Design & Characteristics13 min.
Justin dives into the design rules that make fact tables reliable and easy to work with. You’ll learn what belongs in a fact table, how to choose the right grain, and how keys and relationships should be handled so measures behave predictably. This module helps you build fact tables that support clean calculations and scale well as data grows.
Module 05 - Dimension Table Design & Characteristics17 min.
Now you’ll focus on the tables that give your model clarity and usability. Justin explains what makes a dimension “good”, descriptive columns, stable keys, and a structure that supports filtering and drilling without confusion. You’ll also learn common dimension patterns and best practices that keep models readable, consistent, and friendly for end users.
Module 06 - Advanced Concepts in Star Schemas5 min.
With the basics in place, Justin introduces advanced modeling ideas that solve real-world challenges. You’ll explore more complex relationship scenarios, modeling trade-offs, and patterns that help keep your model both accurate and performant. The goal here is to expand your toolkit without breaking the simplicity that makes star schemas so powerful.
Module 07 - Behavioral Dimensions8 min.
Not all dimensions behave the same way, and this module shows you why that matters. Justin explains how certain dimensions can change the “behavior” of measures depending on how they filter the model, and how to design for those scenarios intentionally. You’ll learn how to anticipate the impact of dimension design choices so your reports stay consistent and trustworthy.
Module 08 - Advanced Concepts (Continued)7 min.
Continue building on the advanced patterns introduced earlier, with deeper examples and practical guidance. Justin reinforces how to handle tricky modeling cases while keeping your structure understandable. This module helps you think like a model designer, balancing flexibility, performance, and simplicity as your data needs evolve.
Module 09 - Special Table Types: Bridge Tables & Junk Dimensions10 min.
Some real-world models need a few extra table types to handle messy relationships and “miscellaneous” attributes cleanly. Justin explains when to use bridge tables, often for many-to-many scenarios, and junk dimensions, to group low-cardinality flags and indicators. You’ll learn how these tables solve common problems while keeping the star schema approach intact.
Module 10 - Class Wrap Up3 min.
Bring everything together with a practical recap of the star schema mindset. Justin reviews the key design rules, common pitfalls to avoid, and how to validate that your model is both correct and scalable. You’ll leave with a clearer modeling process you can reuse on your next project, whether you’re building from scratch or fixing an existing model.
Justin Vogel taught high school Advanced Placement® psychology and academic research for 15 years. He holds an MS in Psychology and spent several summers teaching psychology to educators new to the subject. He has also scored AP exams, reviewed textbooks for the Florida Department of Education, and written exam questions for test banks. He has presented at professional learning conferences at the local and national level and now puts his teaching and presentation skills to use on the Power BI team at Pragmatic Works.
