Book Image

Hands-On Business Intelligence with DAX

By : Ian Horne
Book Image

Hands-On Business Intelligence with DAX

By: Ian 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

Creating summary tables

In the last section of this chapter, we're going to take a look at another way you can optimize your data model, through the use of summary tables. Although the use of summary tables will not necessarily help to reduce the size of your data model in terms of memory usage, they are a great way to improve performance, especially if your data model contains large tables with millions of rows. Any visual that uses a summary table will potentially be much faster than if it were working directly with a larger native table.

There are a couple of ways to create summary tables. If you have access to the source database, then you can create summary tables at the source using SQL views. This has the advantage that, if not needed for analysis, you do not need to import the larger table on which the views are based. If you don't need to import the larger table...