Book Image

Microsoft Power BI Complete Reference

By : Devin Knight, Brian Knight, Mitchell Pearson, Manuel Quintana, Brett Powell
Book Image

Microsoft Power BI Complete Reference

By: Devin Knight, Brian Knight, Mitchell Pearson, Manuel Quintana, Brett Powell

Overview of this book

Microsoft Power BI Complete Reference Guide gets you started with business intelligence by showing you how to install the Power BI toolset, design effective data models, and build basic dashboards and visualizations that make your data come to life. In this Learning Path, you will learn to create powerful interactive reports by visualizing your data and learn visualization styles, tips and tricks to bring your data to life. You will be able to administer your organization's Power BI environment to create and share dashboards. You will also be able to streamline deployment by implementing security and regular data refreshes. Next, you will delve deeper into the nuances of Power BI and handling projects. You will get acquainted with planning a Power BI project, development, and distribution of content, and deployment. You will learn to connect and extract data from various sources to create robust datasets, reports, and dashboards. Additionally, you will learn how to format reports and apply custom visuals, animation and analytics to further refine your data. By the end of this Learning Path, you will learn to implement the various Power BI tools such as on-premises gateway together along with staging and securely distributing content via apps. This Learning Path includes content from the following Packt products: • Microsoft Power BI Quick Start Guide by Devin Knight et al. • Mastering Microsoft Power BI by Brett Powell
Table of Contents (25 chapters)
Title Page
About Packt
Contributors
Preface
Index

DAX measures


All analytical expressions ranging from simple sums and averages to custom, complex statistical analyses are implemented within DAX measures. Most measure expressions will reference and aggregate the numeric columns of fact tables, which are hidden from the Report View, as we have seen in per the previous chapter. Additional DAX measures can include filtering conditions which supplement or override any filters applied in Power BI reports, such as the net sales amount for first-year customers only. Measures can also evaluate text columns from dimension tables, such as the count of states or provinces with sales and return text and date values.

Just like the M query language, DAX is a rich, functional language that supports variables and external expression references. Multiple variables can be defined within a DAX measure to improve readability, and the results of other measures can be referenced as well, such as the Plan Grain Status measure in Chapter 9, Designing Import and...