Book Image

Microsoft Power BI Performance Best Practices

By : Bhavik Merchant
Book Image

Microsoft Power BI Performance Best Practices

By: Bhavik Merchant

Overview of this book

This book comprehensively covers every layer of Power BI, from the report canvas to data modeling, transformations, storage, and architecture. Developers and architects working with any area of Power BI will be able to put their knowledge to work with this practical guide to design and implement at every stage of the analytics solution development process. This book is not only a unique collection of best practices and tips, but also provides you with a hands-on approach to identifying and fixing common performance issues. Complete with explanations of essential concepts and practical examples, you’ll learn about common design choices that affect performance and consume more resources and how to avoid these problems. You’ll grasp the general architectural issues and settings that broadly affect most solutions. As you progress, you’ll walk through each layer of a typical Power BI solution, learning how to ensure your designs can handle scale while not sacrificing usability. You’ll focus on the data layer and then work your way up to report design. We will also cover Power BI Premium and load testing. By the end of this Power BI book, you’ll be able to confidently maintain well-performing Power BI solutions with reduced effort and know how to use freely available tools and a systematic process to monitor and diagnose performance problems.
Table of Contents (21 chapters)
Part 1: Architecture, Bottlenecks, and Performance Targets
Part 2: Performance Analysis, Improvement, and Management
Part 3: Fetching, Transforming, and Visualizing Data
Part 4: Data Models, Calculations, and Large Datasets
Part 5: Optimizing Premium and Embedded Capacities


As we have seen in this chapter, interacting with analytical reports is very similar to other web applications, so the user's level of engagement and satisfaction can be measured in similar ways. Studies of user interfaces and web browsing suggest that a report that is generated in less than 4 seconds is ideal. They also suggest that reports completing in 10-12-second durations or higher should be considered carefully as this is the point of user frustration.

You should set performance targets and be prepared for outliers by measuring against the 90th percentile (P90). Success may still require setting the right expectations by having different targets if you have highly complex reports.

It is important to remember that each component of Power BI and even the network itself can contribute to performance issues. Therefore, performance issues cannot be solved in isolation (for example, by only adjusting reports). This may require coordination with multiple teams and external vendors, particularly in large organizations.

In the next chapter, we will focus on the internal VertiPaq Storage Engine in Power BI to learn how to we can get it to optimize storage for us. We will also look at gateway optimization and general architectural advice to make sure the environment does not become a bottleneck.