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)
1
Section 1: Data Modeling in Power BI
4
Section 2: Data Preparation in Query Editor
10
Section 3: Data Modeling
13
Section 4: Advanced Data Modeling

Chapter 9: Star Schema and Data Modeling Common Best Practices

In the previous chapter, we learned a lot about data modeling components in Power BI Desktop, including table and field properties. We also learned about the feature tables and how they make a table from our data model accessible across the organization. We then learned how to build summary tables with DAX. Then we looked at the relationships in more detail; we learned about different relationship cardinalities, filter propagation, and bidirectional relationships. In this chapter, we look at some star schema and data modeling best practices, including the following:

  • Dealing with many-to-many relationships
  • Being cautious with bidirectional relationships
  • Dealing with inactive relationships
  • Using configuration tables
  • Avoiding calculated columns when possible
  • Organizing the model
  • Reducing model size by disabling auto date/time

In this chapter, we use the Chapter 9, Star Schema and Data...