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)
Section 1: Introduction to DAX for the BI Pro
Section 2: Understanding DAX Functions and Syntax
Section 3: Taking DAX to the Next Level


In this chapter, we learned about some of the techniques we can use to help us optimize our data models. We learned that reducing a data model's memory requirement is a major consideration in the overall design process.

We started off by learning about the VertiPaq compression engine. We looked at what it is and how it works, and why this knowledge is essential if we want to effectively optimize our data models. Next, we learned about data profiling, and how this can help us identify what data to include in a data model. This included a look at the data profiling capabilities of Power BI Desktop, along with some other tools that are available to help with this process.

We then learned about some of the ways we can simplify the structure of our data models looking at column cardinality, column storage, and identifying the correct columns to store. Finally, we looked...