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

Calculation groups

Calculation groups are a data modeling feature that enable common expression logic to be centralized and leveraged by other measures when needed in reports. In this section, we cover the creation of the same basic date intelligence from the previous section, Date intelligence metrics, but use calculation groups.

In the previous section, we covered the creation of basic date intelligence metrics for Internet Net Sales. However, supporting eight common date intelligence expressions for each of 24 base measures would imply adding 192 (8*24) distinct measures to the dataset, thus adding both development time and complexity for report authors and analysts. Calculation groups address this issue by allowing report authors to reuse common expressions such as year-to-date for whichever base measure it’s needed for.

Calculation groups allow the creation of general calculation formulas that can be applied to any explicit measure within the data model. Thus...