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

General architectural guidance

This section presents general architectural best practices that can help with performance.

Planning data and cache refresh schedules

A sometimes-overlooked consideration is how fresh an Import dataset's sources are. There is no point refreshing a dataset multiple times a day if it relies on an external data mart that is only refreshed nightly. This adds an unnecessary load to data sources and the Power BI service.

Look at your environment to see when refresh operations are happening and how long they are taking. If many are happening in parallel, this could slow down other operations due to intense CPU and memory usage. The effect can be larger with Power BI Premium. Consider working with dataset owners to remove unnecessary refreshes or change timings so that they do not occur altogether, but are potentially staggered instead. A data refresh in progress can require as much additional memory as the dataset itself, sometimes more if the...