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

Chapter 3: DirectQuery Optimization

Until now, we have looked at Power BI performance from a relatively high level. You have learned which areas of Power BI performance can be impacted by your design decisions and what to consider when making these choices. These decisions were architectural, so were about choosing the right components to ensure the most efficient movement of data to suit your data volume and freshness requirements.

However, this knowledge alone is not sufficient and will not guarantee good performance. With the gateways in the previous chapter, we saw how a single component of the solution can be configured and optimized quite heavily. This applies to most of the other areas of Power BI, so now we will begin to deep dive into how specific design decisions in each area affect user experience and what configurations should be avoided.

In Chapter 2, Exploring Power BI Architecture and Configuration, we looked at storage modes for Power BI datasets and learned...