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

Gateway architectures


For large-scale deployments of Power BI in which multiple types of datasets and workloads will be supported (import refreshes, as well as DirectQuery and Live connection queries), BI teams can consider multiple gateway clusters. In this approach, each gateway cluster is tailored to meet the specific resource needs (RAM and CPU) of the different workloads, such as large nightly refreshes or high volumes of concurrent queries in the early mornings.

For example, one gateway cluster could be composed of two gateway instances with a relatively high amount of available RAM on each gateway server. This cluster would have resources available during the most intensive scheduled refresh operations (for example, 4 A.M. to 6 A.M.) and would be exclusively used by import mode Power BI datasets and any Azure Analysis Services models that also regularly import data from on-premises sources. A separate gateway cluster would be created based on two gateway instances with a relatively...