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. You'll get to know how to choose between Power Query and Power BI, learn about facts, dimensions, and their relationships, explore the use of quick measures and hierarchies, and write DAX to fully customize your data model. Some best practices are also discussed to improve the performance of your reports. You'll apply all of this on real-world datasets, issued by the United States Census Bureau.
Proper 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, using both Power BI and Power Query.
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. Afterwards, you'll continue with an extension of the star schema: the snowflake schema.
You'll extend your data modeling skills further by adding more tables and relationships. In addition, you'll learn how to use hierarchies and explore several granularity levels of your data.
In this final chapter, you'll look at some advanced data modeling techniques. You'll learn how and when to use bi-directional cross filters and role-playing dimensions. To complete the course, you'll study performance optimization tips and tricks in Power BI.
PrerequisitesIntroduction to Power BI
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