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


In this chapter, we learned how to deal with exceptionally large volumes of data. The first use case was where we had Power BI datasets growing beyond the 1 GB storage limit that's available to Power BI Pro users in the Shared capacity. In such cases, we recommended considering Power BI Premium. The dataset limit in Premium is 10 GB. With the large dataset storage format enabled, we learned that datasets could grow well beyond this size. Technically, we can use all the available memory on the capacity, which is 400 GB on a Premium P5 capacity. Larger Premium capacities also have higher concurrency limits, which can give us better refresh and query performance.

Then, we looked at a case where the scale problem comes from concurrent users and learned why this can put pressure on memory and CPU resources. We introduced AAS as a solution to this problem due to its ability to leverage QSO. We also recommended using partitions on Premium and AAS to speed up refreshes on...