The goal of this first part of the book is to bring everybody onto the same page when it comes to the topic of data modeling. The chapters in this part are agnostic: the content, problems, and solutions are not specific to a particular type of database management system. You will be able to apply the knowledge you gain from this part to any relational or analytical database. This includes, of course, Power BI, Analysis Services tabular and Azure SQL DB, but is not limited to them, and you can apply all statements, information, and conclusions to database management systems from vendors other than Microsoft—to classical cubes, to data lakehouses, and so on.
These concepts have existed for decades and are so mature that I bet they’ll be around for decades to come. Make sure to learn of all them so you’ll understand why I insist on applying one transformation or another when it comes to data modeling in Power BI in the later parts of this book.
Chapter 1 introduces the following basic terms and concepts:
Entities and tables
Relations and their cardinality
Primary and foreign keys
You’ll learn how to combine information spread out into different tables with the help of Set operators and join operators, including problems you might face that, for example, could result in missing data or duplication of data. I discuss the three core possibilities ...
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