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

M Query examples


The M query language includes hundreds of functions and several books have been written about to its application. The greater purpose of this chapter is to understand M queries in the context of a corporate Power BI solution that primarily leverages an IT-managed data warehouse. As shown in the examples shared in the M Queries section earlier, the combination of a mature data warehouse and a layer of SQL view objects within this source may eliminate any need for further data transformations. However, Power BI Dataset designers should still be familiar with the fundamentals of M queries and their most common use cases, as it's often necessary to further extend and enhance source data. 

The following sections demonstrate three common data transformation scenarios that can be implemented in M. Beyond retrieving the correct results, the M queries also generate SQL statements for execution by the source system via query folding, and comments are included for longer-term maintenance...