Data Modeling in Power BI
Learn the key concepts of data modeling on Power BI.
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Course Description
Foundations of Data Modelling
Proper data modeling is the foundation of data analysis and creating reports in Power BI. This course lets you explore a toolbox of data cleaning, shaping, and loading techniques, which you can apply to your data.Diving into Power Query
You'll get to know how to choose between Power Query and Power BI, and discover the foundations of data modeling by going into star and snowflake schemas. You'll apply all of this to real-world datasets issued by the United States Census Bureau.- 1
Defining Tables
FreeProper data analysis relies on proper data modeling. This first chapter covers the basic concepts and teaches you how to set up and load data from multiple sources.
- 2
Shaping Tables
In this chapter, we continue comparing Power Query and Power BI practices. Later, you will exercise combining tables and column extraction on Power BI.
- 3
Dimensional Modeling
In this chapter, you'll learn more about one of the most popular approaches to data modeling. You'll get familiar with the basic building blocks of the dimensional model; facts, dimensions, and star schemas.
- 4
Star and Snowflake schemas
In this final chapter, you'll continue with an extension of the star schema: the snowflake schema. Lastly, you will have your first practice with performance analyzer in Power BI.
Collaborators
Prerequisites
Introduction to Power BISara Billen
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Data Scientist at DataCamp
Sara is a graduate of a master's degree in Business Engineering and Marketing Analysis. Prior to working at DataCamp she worked as a Data Science consultant for a Belgian IT company. Sara is passionate about education, data science, and business and loves that she is able to combine all of these disciplines in her job at DataCamp.
Maarten Van den Broeck
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Senior Content Developer at DataCamp
Maarten is an aquatic ecologist and teacher by training and a data scientist by profession. He is also a certified Power BI and Tableau data analyst. After his career as a PhD researcher at KU Leuven, he wished that he had discovered DataCamp sooner. He loves to combine education and data science to develop DataCamp courses. In his spare time, he runs a symphonic orchestra.
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