Book Image

Hands-On Business Intelligence with DAX

By : Horne
Book Image

Hands-On Business Intelligence with DAX

By: Horne

Overview of this book

Data Analysis Expressions (DAX) is known for its ability to increase efficiency by extracting new information from data that is already present in your model. With this book, you’ll learn to use DAX’s functionality and flexibility in the BI and data analytics domains. You’ll start by learning the basics of DAX, along with understanding the importance of good data models, and how to write efficient DAX formulas by using variables and formatting styles. You’ll then explore how DAX queries work with the help of examples. The book will guide you through optimizing the BI workflow by writing powerful DAX queries. Next, you’ll learn to manipulate and load data of varying complexity within Microsoft products such as Power BI, SQL Server, and Excel Power Pivot. You’ll then discover how to build and extend your data models to gain additional insights, before covering progressive DAX syntax and functions to understand complex relationships in DAX. Later, you’ll focus on important DAX functions, specifically those related to tables, date and time, filtering, and statistics. Finally, you’ll delve into advanced topics such as how the formula and storage engines work to optimize queries. By the end of this book, you’ll have gained hands-on experience in employing DAX to enhance your data models by extracting new information and gaining deeper insights.
Table of Contents (18 chapters)
1
Section 1: Introduction to DAX for the BI Pro
7
Section 2: Understanding DAX Functions and Syntax
14
Section 3: Taking DAX to the Next Level

Dealing with relationships

In Chapter 3, Building Data Models, we looked at creating physical relationships between tables as part of our look at data modeling. For example, in our data model, we have a physical relationship defined between the Product and Sales tables, as shown in Figure 6-1:

Figure 6-1: The one-to-many relationship between the Product and Sales tables

A physical relationship in a data model requires that at least one side of the relationship is linked to a column in a table that contains unique values. In the preceding example, we've built the relationship using the ProductKey column of the Product table linked to the ProductKey column of the Sales table, creating a one-to-many relationship.

With this relationship, any filters applied to columns of the Product table are propagated using a filter on the Sales table. The list of values filtered in the ProductKey...