Data Modeling in Power BI
Learn the key concepts of data modeling on Power BI.
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Course Description
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.
- 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, using both Power BI and Power Query.
Data modeling and table properties50 xpPower Query vs. Power BI50 xpLoad and transform data50 xpLoading a CSV100 xpRounding, replacement, and sorting100 xpData categorization and visibility100 xpWorking with string columns100 xpShaping tables50 xpPower Query vs. Power BI again100 xpMerging and appending queries50 xpBreaking a file into multiple tables100 xpAppending files100 xpColumn extraction100 xp - 2
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. Afterwards, you'll continue with an extension of the star schema: the snowflake schema.
Dimensional modeling50 xpFacts vs. dimensions100 xpCreating a star schema50 xpSplitting data into facts and dimensions100 xpLoad a new dimension100 xpCreate another dimension100 xpStar and snowflake schemas50 xpSnowflake vs. star schema50 xpEvaluating performance50 xpStar schemas100 xpSnowflake schemas100 xpThe performance analyzer100 xp - 3
Extending the Kimball Model
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.
Date dimensions and relationships50 xpCardinality50 xpDate dimensions and relationships in Power BI50 xpCreate a year dimension100 xpExtend the year dimension100 xpComposite key relationships100 xpGranularity, measures, and hierarchies50 xpHidden hierarchies100 xpHierarchies and measures in Power BI50 xpBuild a hierarchy100 xpChange the granularity of a query100 xpMeasures and quick measures100 xp - 4
Advanced Data Modeling
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.
Working with relationships50 xpBi-directional relationships50 xpCross-filtering and role-playing dimensions50 xpBi-directional cross-filtering100 xpRole-playing dimensions100 xpIdentifying performance problems50 xpOptimizing performance100 xpPerformance tips in Power BI50 xpData types and calculations100 xpCalculated versus computed columns100 xpAn alternative to bi-directional filtering100 xpCongratulations!50 xp
Kevin Feasel
Lis Sulmont
Carl RosseelPrerequisites
Introduction to Power BI
Maarten Van den Broeck
Content Developer at DataCamp
Maarten is an aquatic ecologist and teacher by training and a data scientist by profession. After his career as a Ph.D. researcher at KU Leuven, he wished that he had discovered DataCamp sooner. He loves to combine education and data science to develop DataCamp courses.
Sara Billen
Curriculum Manager 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 as curriculum manager at DataCamp.
What do other learners have to say?
“I've used other sites—Coursera, Udacity, things like that—but DataCamp's been the one that I've stuck with.”
Devon Edwards Joseph
Lloyds Banking Group
“DataCamp is the top resource I recommend for learning data science.”
Louis Maiden
Harvard Business School
“DataCamp is by far my favorite website to learn from.”
Ronald Bowers
Decision Science Analytics, USAA
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