Book Image

Mastering Microsoft Power BI – Second Edition - Second Edition

By : Gregory Deckler, Brett Powell
4.5 (2)
Book Image

Mastering Microsoft Power BI – Second Edition - Second Edition

4.5 (2)
By: Gregory Deckler, Brett Powell

Overview of this book

Mastering Microsoft Power BI, Second Edition, provides an advanced understanding of Power BI to get the most out of your data and maximize business intelligence. This updated edition walks through each essential phase and component of Power BI, and explores the latest, most impactful Power BI features. Using best practices and working code examples, you will connect to data sources, shape and enhance source data, and develop analytical data models. You will also learn how to apply custom visuals, implement new DAX commands and paginated SSRS-style reports, manage application workspaces and metadata, and understand how content can be staged and securely distributed via Power BI apps. Furthermore, you will explore top report and interactive dashboard design practices using features such as bookmarks and the Power KPI visual, alongside the latest capabilities of Power BI mobile applications and self-service BI techniques. Additionally, important management and administration topics are covered, including application lifecycle management via Power BI pipelines, the on-premises data gateway, and Power BI Premium capacity. By the end of this Power BI book, you will be confident in creating sustainable and impactful charts, tables, reports, and dashboards with any kind of data using Microsoft Power BI.
Table of Contents (18 chapters)
16
Other Books You May Enjoy
17
Index

Query folding

Query folding is one of the most powerful and important capabilities of the M language as it translates M expressions into equivalent query statements for the given source system to process. With query folding, Power Query (M) serves as a rich abstraction layer for defining both simple and complex data transformation processes while still leveraging the compute resources of the source system. When implementing any remaining logic or data transformations via M functions, a top priority of the dataset designer is to ensure that these operations are folded to the data source.

In the following M query shown in Figure 2.1, a Table.RemoveColumns() M function is applied against the SQL view for the Internet Sales fact table to exclude three columns that are not needed for the dataset:

Graphical user interface, application  Description automatically generated

Figure 2.1: Power Query Editor: View Native Query

The additional step is translated to a SQL query that simply doesn’t select the three columns. The specific SQL statement...