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

Optimizing performance


One of the main reasons for creating a dataset, particularly an import mode dataset, is to provide a performant data source for reports and dashboards. Although Power BI supports traditional reporting workloads, such as email subscriptions and view-only usage, Power BI empowers users to explore and interact with reports and datasets. The responsiveness of visuals for this self-service workload is largely driven by fundamental data model design decisions, such as the granularity of fact and dimension tables. 

Additional performance factors outside the scope of this chapter include the hardware resources allocated to the dataset, such as with Power BI Premium capacities (v-cores, RAM), the efficiency of the DAX Measures created for the dataset, the design of the Power BI reports that query the dataset, and the volume and timing of queries generated by users. Beyond the DAX measures described in Chapter 10Developing DAX Measures and Security Roles these other factors...