What will I actually learn in this Power BI data modeling course?

You'll learn how to build and refine Power BI data models so they support clearer analysis and better report performance. It starts with how tables relate to each other and how schema design works, then builds into DAX calculations and performance tuning. Along the way, you'll practice tasks like setting up a star schema and adding measures to answer business questions.

Do I need Power BI experience before taking this course?

No, prior Power BI experience isn't required. The course includes setting up Power BI Desktop and starts with the basics of models, schemas, and relationships before moving into DAX. Some comfort working with tables and columns will help, because it moves fairly quickly into calculations and model design.

Is this course beginner-friendly for Power BI data modeling?

Yes, it's beginner-friendly for learners who are new to Power BI data modeling. The course starts with core ideas like schemas, relationships, and model views, then reinforces them with guided exercises, readings, and quizzes before moving into DAX and optimization. It may feel more technical if you're completely new to how data tables relate, but it doesn't assume advanced experience.

How long does it take to complete this course?

Expect about 25 hours of work in total. At around 10 hours a week, that's about 3 weeks of steady study. The course includes lessons, readings, guided exercises, quizzes, and a final applied assessment.

Are there hands-on exercises or projects in this course?

Yes, there is hands-on practice, though it's mostly guided exercises rather than a large independent project. You'll work through tasks like configuring a star schema, adding calculated columns and measures, and setting up time intelligence with a common date table. There's also a final applied assessment, so you apply each idea as you learn it and then bring the skills together.

What skills and topics are covered in this course?

The course focuses on data model design, DAX calculations, and performance improvement in Power BI. You'll work with relationships and schemas, create measures and time-based calculations, and learn how modeling choices affect report behavior. The bigger takeaway is how to organize data so analysis stays accurate and reports stay usable as the model grows.

What can I actually do after finishing this course?

After finishing, you should be able to build a Power BI model that supports analysis, write core DAX calculations, and troubleshoot some common performance issues. For example, you could connect fact and dimension tables, create measures for revenue or year-over-year comparisons, and adjust model settings to improve report responsiveness. That's a solid scope if you want to move beyond importing data and start shaping it for analysis.

Is this course more conceptual or hands-on?

It's more concept-first with guided practice than project-heavy. The course spends time explaining how relationships, DAX, and optimization choices work, then reinforces that through exercises, quizzes, and a final applied task. It suits learners who want to understand the logic behind a model, not just reproduce steps.

Why choose this course over other Power BI data modeling courses?

This course is a strong choice if you want to focus on the model behind Power BI reports, not just the report layer itself. It moves from relationships and schema choices into DAX, time intelligence, and performance tuning, with guided exercises and a final assessment that pull those pieces together. If you want beginner-level instruction that helps you build, maintain, and optimize Power BI models, and you'd like that work to support PL-300 prep, this course is a good fit.

Data Modeling in Power BI

This course is part of Microsoft Power BI Data Analyst Professional Certificate

Instructor: Microsoft

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4 modules

Gain insight into a topic and learn the fundamentals.

825 reviews

Beginner level

Recommended experience

Flexible schedule

3 weeks at 10 hours a week

Learn at your own pace

89%

Most learners liked this course

4 modules

Gain insight into a topic and learn the fundamentals.

825 reviews

Beginner level

Recommended experience

Flexible schedule

3 weeks at 10 hours a week

Learn at your own pace

89%

Most learners liked this course

What you'll learn

How to form a model using a Star Schema.
How to write calculations DAX to create elements and analysis in Power BI.
How to optimize performance in a Power BI model.

Skills you'll gain

Tools you'll learn

Power BI

Details to know

Shareable certificate

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Assessments

22 assignments

Taught in English

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Build your Data Analysis expertise

This course is part of the Microsoft Power BI Data Analyst Professional Certificate

When you enroll in this course, you'll also be enrolled in this Professional Certificate.

Learn new concepts from industry experts
Gain a foundational understanding of a subject or tool
Develop job-relevant skills with hands-on projects
Earn a shareable career certificate from Microsoft

There are 4 modules in this course

This course forms part of the Microsoft Power BI Analyst Professional Certificate. This Professional Certificate consists of a series of courses that offers a good starting point for a career in data analysis using Microsoft Power BI.

In this course, you'll learn how to use Power BI to create and maintain relationships in a data model and form a model using multiple Schemas. You'll explore the basics of DAX, Power BI's expression language, and add calculations to your model to create elements and analysis in Power BI. You'll discover how to configure the model to support Power BI features for insightful visualizations, analysis, and optimization. After completing this course you'll be able to: ● Create and maintain relationships in a data model. ● Form a model using a Star Schema ● Write calculations DAX to create elements and analysis in Power BI ● Create calculated columns and measures in a model ● Perform useful time intelligence calculations in DAX ● Optimize performance in a Power BI model This is also a great way to prepare for the Microsoft PL-300 exam. By passing the PL-300 exam, you’ll earn the Microsoft Power BI Data Analyst certification.

Module details

In this module, you will explore the foundational concepts of data modeling in Power BI, including different schema types and their applications. You will learn how to create and manage relationships within data models, understand cardinality and cross-filtering, and apply Star schema design principles. By the end of this module, you will be able to structure efficient and scalable data models for analysis.

What's included

13 videos21 readings4 assignments1 discussion prompt

13 videosTotal 68 minutes

Course introduction4 minutes
Introduction to data models5 minutes
Introduction to schemas6 minutes
Setting up a Flat schema in Power BI5 minutes
Understanding fact and dimension tables4 minutes
Introduction to cardinality5 minutes
Introduction to cross-filter direction5 minutes
Defining data granularity6 minutes
Setting up a Star schema in Power BI6 minutes
Setting up a Snowflake schema6 minutes
Why it is important to use Snowflake schema4 minutes
Resolving challenges in data models5 minutes
Module summary: Concepts for data modeling6 minutes

21 readingsTotal 275 minutes

Course syllabus10 minutes
How to be successful in this course10 minutes
Setting up your Power BI environment10 minutes
New name for Power BI datasets10 minutes
Additional resources: Concepts for data modeling5 minutes
Model view in Power BI15 minutes
Schemas cheatsheet10 minutes
Table and column properties cheatsheet10 minutes
Exercise: Configuring a Flat schema30 minutes
Exemplar: Configuring a Flat schema10 minutes
Activity: Configure a Flat schema with multiple sources30 minutes
Additional resources: Introduction to data models5 minutes
Normalization and denormalization10 minutes
Managing model relationships10 minutes
Model relationships cheatsheet10 minutes
Additional resources: Introduction to cardinality and cross-filter direction5 minutes
Exercise: Configuring a Star schema30 minutes
Exemplar: Configuring a Star schema10 minutes
Activity: Changing your Star schema into a Snowflake schema30 minutes
Data View in Power BI10 minutes
Additional resources: Working with advanced data models5 minutes

4 assignmentsTotal 85 minutes

Module quiz: Concepts for data modeling30 minutes
Knowledge check: Introduction to data models15 minutes
Knowledge check: Introduction to cardinality and cross-filter direction15 minutes
Knowledge check: Working with advanced data models25 minutes

1 discussion promptTotal 10 minutes

Why is data modeling important in the data analysis process?10 minutes

This module focuses on building analytical capabilities using DAX in Power BI. You will learn how to write calculations, create calculated columns and measures, and apply context-aware logic for analysis. Additionally, you will explore time intelligence functions to perform period-based comparisons and business analysis. By the end, you will be able to use DAX effectively to enhance data models and generate insights.

What's included

23 videos21 readings10 assignments1 discussion prompt

23 videosTotal 113 minutes

Introduction to Data Analysis Expressions (DAX)6 minutes
Formulas and functions in DAX5 minutes
Row context and filter context6 minutes
Introduction to calculated tables5 minutes
Creating calculated columns5 minutes
Introduction to measures5 minutes
Types of measures5 minutes
Basic statistical functions5 minutes
DAX measures and context in business4 minutes
Creating quick measures6 minutes
Creating custom measures with DAX4 minutes
Introduction to the CROSSFILTER function5 minutes
Using CALCULATE with filters5 minutes
Introduction to role-playing dimensions6 minutes
Introduction to the USERELATIONSHIP function5 minutes
Configuring role-playing dimensions3 minutes
The importance of time intelligence5 minutes
Using DAX for summarization over time6 minutes
Using DAX for comparison over time5 minutes
Setting up a common date table using DAX5 minutes
Setting up a common date table with M and Power Query4 minutes
Time intelligence in business3 minutes
Module summary: Using DAX in Power BI7 minutes

21 readingsTotal 305 minutes

DAX cheatsheet10 minutes
Cloning and calculating tables10 minutes
DAX table functions10 minutes
Exercise: Adding a calculated table and column30 minutes
Exemplar: Adding a calculated table and column10 minutes
Additional resources: Introduction to DAX5 minutes
Statistical functions cheatsheet10 minutes
Additional resources: Introduction to measures5 minutes
Exercise: Adding a measure30 minutes
Exemplar: Adding a measure10 minutes
Filter functions in CALCULATE10 minutes
Activity: Using the CALCULATE function30 minutes
Additional resources: Working with measures5 minutes
Exercise: Adding a role-playing dimension30 minutes
Exemplar: Adding a role-playing dimension10 minutes
Additional resources: DAX and table relationships5 minutes
Additional time intelligence functions10 minutes
Exercise: Using time intelligence to compare to previous year30 minutes
Exemplar: Using time intelligence to compare to previous year10 minutes
Activity: Set up a common date table30 minutes
Additional resources: Time intelligence and calculations in DAX5 minutes

10 assignmentsTotal 185 minutes

Module quiz: Using DAX in Power BI50 minutes
Self-review: Adding a calculated table and column15 minutes
Knowledge check: Using Data Analysis Expressions (DAX) in Power BI15 minutes
Knowledge check: Introduction to measures15 minutes
Self-review: Adding a measure10 minutes
Knowledge check: Working with measures15 minutes
Self-review: Adding a role-playing dimension15 minutes
Knowledge check: DAX and table relationships15 minutes
Self-review: Using time intelligence to compare to previous year10 minutes
Knowledge check: Time intelligence calculations in DAX25 minutes

1 discussion promptTotal 10 minutes

Which DAX features did you find most useful?10 minutes

In this module, you will learn how to improve the performance of Power BI data models by identifying inefficiencies and applying optimization techniques. You will explore methods such as reducing cardinality, optimizing metadata, improving DirectQuery performance, and managing aggregations. By the end, you will be able to enhance model efficiency and ensure faster, scalable data processing.

What's included

10 videos12 readings6 assignments1 discussion prompt

10 videosTotal 59 minutes

What is optimization and why is it necessary?7 minutes
Optimization by example7 minutes
Identifying and reducing cardinality levels6 minutes
Resolving performance issues in the data model5 minutes
Behavior and limitations of DirectQuery connections7 minutes
Optimizing DirectQuery performance with query reductions4 minutes
Optimizing DirectQuery performance with table storage6 minutes
What are aggregations and why use them?6 minutes
Creating an aggregation6 minutes
Module summary: Optimize a model for performance in Power BI8 minutes

12 readingsTotal 165 minutes

Exercise: Improving data model performance30 minutes
Exemplar: Improving data model performance10 minutes
Optimizing columns and metadata10 minutes
Optimizing the Auto date/time feature10 minutes
Activity: Optimizing the columns and Auto date/time30 minutes
Additional resources: Optimize performance in a Power BI model5 minutes
Walk-through: Optimizing a DirectQuery model10 minutes
Additional resources: Optimize DirectQuery models5 minutes
Exercise: Adding an aggregation30 minutes
Exemplar: Adding an aggregation10 minutes
How to manage aggregations step-by-step 10 minutes
Additional resources: Create and manage aggregations5 minutes

6 assignmentsTotal 120 minutes

Module quiz: Optimize a model for performance in Power BI50 minutes
Self-Review: Improving data model performance15 minutes
Knowledge check: Optimize a model for performance in Power BI15 minutes
Knowledge check: Optimize DirectQuery models15 minutes
Self-review: Adding an aggregation10 minutes
Knowledge check: Create and manage aggregations15 minutes

1 discussion promptTotal 10 minutes

How would performance and optimization impact different stakeholders?10 minutes

In this module, you will apply your knowledge of data modeling, DAX, and performance optimization to complete a comprehensive project. You will build and refine a data model, demonstrating your ability to design, analyze, and optimize it effectively. This module reinforces your learning through practical application and prepares you for real-world data analysis tasks.