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

Dealing with many-to-many relationships

In the previous chapter, Chapter 8, Data Modeling Components, we discussed different relationship cardinalities. We went through some scenarios to understand the one-to-one, one-to-many, and many-to-many cardinalities. We showed an example of creating a many-to-many relationship between two tables using non-key columns. While creating a relationship with many-to-many cardinality may work for smaller and less complex data models, it can cause some severe issues if we do not precisely know what we are doing. In some cases, we may get incorrect results in totals; we might find some missing values or get poor performance in large models; while in other cases, we may find the many-to-many cardinality very useful. The message here is that, depending on the business case, we may or may not use many-to-many cardinality; it depends on what works the best for our model while satisfying the business requirements. For instance, the many-to-many cardinality...