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 defined basic data modeling as a process where you choose which data attributes are grouped into entities and how those entities are related to one another. We learned that for DirectQuery, transformations in Power Query should be kept simple to avoid generating overly complex query statements for the external source system. We also learned how to use the native query viewing feature in Power Query to see the exact query Power BI will use. We saw how transformations can also be translated to native query language.

We learned that Power BI is flexible enough to allow you to define your own relationships across DirectQuery tables not necessarily matching those already in the data source. This must be used with care and some planning. It is better to leverage relationships and referential integrity that are already defined in the external data source where possible as these are likely already optimized for joining and filtering. We also explored relationship...