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

Understanding DAX pitfalls and optimizations

Before we dive into specific DAX improvements, we will briefly review the following suggested process to tune your DAX formulas.

The process for tuning DAX

In Chapter 5, Desktop Performance Analyzer, and Chapter 6, Third-Party Utilities, we provided detailed information and examples of how to use various tools to measure performance. We'll take this opportunity to remind you of which tools can help with DAX tuning and how they can be used. A recommended method to tune DAX is as follows:

  1. Review the DAX expressions in the dataset. Ideally, run the Best Practice Analyzer (BPA) to identify potential DAX improvements. The BPA does cover some of the guidance provided in the next section, but it's a good idea to check all the rules manually.
  2. Rank the suggestions in terms of estimated effort, from lowest to highest. Consider moving some calculations or even intermediate results to Power Query. This is usually a better...