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

Implementing roleplaying dimensions

The roleplaying dimension is one of the most common scenarios we face in data modeling. The term was inherited from multidimensional modeling within the SQL Server Analysis Services Multidimensional. Before jumping to the implementation part, let's take a moment and understand what the roleplaying dimension is. When we create multiple relationships between a fact table and a dimension for logically distinctive roles, we use the concept of a roleplaying dimension. The most popular roleplaying dimensions are the Date and Time dimensions. For instance, we may have multiple dates in a fact table such as Order Date, Due Date, and Ship Date, which participate in different relationships with the Date dimension. Each date represents a different role in our analysis. In other words, we can analyze the data using the Date dimension for different purposes. For instance, we can calculate Sales Amount by Order Date, which results in different values from...