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

Model metadata


The consistent and complete application of metadata properties, such as Default Summarization and Data Category, greatly affect the usability of a dataset. With a solid foundation of tables, column data types, and relationships in place, dataset designers and BI teams should consider all primary metadata properties and their implications for user experience as well as any additional functionality they can provide.

Visibility

Every table, column, and measure that isn't explicitly needed in the Report View should be hidden. This usually includes all relationship columns and any measure support tables and measure expressions.

If a column is rarely needed or only needed for a specific report, it can be temporarily unhidden to allow for this report to be developed and then hidden again to maximize usability. Numeric fact table columns that are referenced by DAX Measures (for example, quantity) should be hidden from the fields list, as the measures can be used for visualizing this...