Data Modeling with Microsoft Power BI

Preface

Welcome to this journey into data modeling concepts and practical examples for Power BI, including DAX, Power Query and T-SQL. This book is your companion on your journey to gain a comprehensive understanding about the steps needed to make building reports in Power BI Desktop and Power BI Report Builder, and creating measures in DAX, easier.

Power BI supports a wide variety of data sources (covering databases from different vendors, like Microsoft, Oracle or Teradata; flat files, like CSV, text, or Excel; web services like an https link to a web page, etc.). The only way to get data into Power BI is through Power Query. It’s best practice to add calculations as (explicit) measures in DAX (as opposed to calculated columns in DAX or as columns in Power Query or in the data source). Creating calculated tables in DAX should be an exception; depending on your skills and preferences, you will implement transformations to shape the data model either in Power Query (in the user interface or by writing code in the M language) or in the data source. For example, in the case of a relational data warehouse implemented in Microsoft’s relational database engines, you might use T-SQL in the data warehouse, as laid out in Figure P-1.

The first part of this book, which is written in an agnostic way, introduces the necessary concepts in a general way: you can apply this to any analytical system. The second part of the book explains the properties of a data model in Power BI. The rest of ...