Book Image

Expert Data Modeling with Power BI - Second Edition

By : Soheil Bakhshi
4 (1)
Book Image

Expert Data Modeling with Power BI - Second Edition

4 (1)
By: Soheil Bakhshi

Overview of this book

This book is a comprehensive guide to understanding the ins and outs of data modeling and how to create full-fledged data models using Power BI confidently. In this new, fully updated edition, you'll learn how to connect data from multiple sources, understand data, define and manage relationships between data, and shape data models to gain deep and detailed insights about your organization. As you advance through the chapters, the book will demonstrate how to prepare efficient data models in the Power Query Editor and use simpler DAX code with new data modeling features. You'll explore how to use the various data modeling and navigation techniques and perform custom calculations using the modeling features with the help of real-world examples. Finally, you'll learn how to use some new and advanced modeling features to enhance your data models to carry out a wide variety of complex tasks. Additionally, you'll learn valuable best practices and explore common data modeling complications and the solutions to supercharge the process of creating a data model in Power BI and build better-performing data models. By the end of this Power BI book, you'll have gained the skills you need to structure data coming from multiple sources in different ways to create optimized data models that support high-performing reports and data analytics.
Table of Contents (22 chapters)
1
Section I: Data Modeling in Power BI
4
Section II: Data Preparation in Query Editor
10
Section III: Data Modeling
13
Section IV: Advanced Data Modeling
20
Other Books You May Enjoy
21
Index

Using configuration tables

In many cases, a business wants to analyze some of the business metrics in clusters. Some good examples are analyzing sales by unit price range, analyzing sales by product cost range, analyzing customers by their age range, or analyzing customers by commute distance. In all of these examples, the business does not need to analyze constant values; instead, it is more about analyzing a metric (sales, in the preceding examples) by a range of values.

Some other cases are related to data visualization, such as dynamically changing the color of values when they are in a specific range. An example is to change the values’ color to red in all visuals analyzing sales if the sales value for the data points is less than the average sales over time. This is a relatively advanced analysis that can be reused in our reports to keep visualizations’ color consistent.

In the preceding examples, we need to define configuration tables. In the latter example...