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

Summary

In the last chapter of this book, we looked at some of the techniques and tools that are used to help with analyzing the performance of DAX queries and identify potential problems.

We started off this chapter by learning about the storage and formula engines, the two engines used to process a DAX query. We looked at how they work together to retrieve data from the data model, and then process that data to return a result. We learned about how the logical and physical query plans produced by these query engines can help to identify and resolve performance issues with DAX queries.

Finally, we looked at some tools to help us to investigate the performance of DAX queries. We looked at DAX Studio, SQL Server Profiler, and the Performance Analyzer feature in Power BI Desktop. We learned about using these tools to monitor performance by looking at the output of the query engines...