Book Image

Expert Data Modeling with Power BI

By : Soheil Bakhshi
Book Image

Expert Data Modeling with Power BI

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 data models using Power BI confidently. 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. In this book, you'll explore how to use data modeling and navigation techniques to define relationships and create a data model before defining new metrics and performing custom calculations using modeling features. As you advance through the chapters, the book will demonstrate how to create full-fledged data models, enabling you to create efficient data models and simpler DAX code with new data modeling features. With the help of examples, you'll discover how you can solve business challenges by building optimal data models and changing your existing data models to meet evolving business requirements. 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. 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 reporting and data analytics.
Table of Contents (18 chapters)
Section 1: Data Modeling in Power BI
Section 2: Data Preparation in Query Editor
Section 3: Data Modeling
Section 4: Advanced Data Modeling

Using configuration tables

There are many cases when the business needs 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 the preceding 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 can be to change the color of values in all visuals analyzing sales to red if the sales value for the data points is less than the average sale over time. This is a relatively advanced analysis that can be reused in our reports that keeps the consistency of our data visualization.

For all of the preceding examples, we need to define configuration...