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 1: Setting Targets and Identifying Problem Areas

Many people would consider report performance as the most critical area to focus on when trying to improve the speed of an analytics solution. This is largely true, because it is the most visible part of the system used by pretty much every class of user, from administrators to business executives. However, you will learn that there are other areas of a complete solution that should be considered if performance is to be managed comprehensively. For example, achieving good performance in the reporting layer might be of no consequence if the underlying dataset that powers the report takes a long time to be refreshed or is susceptible to failures due to resource limits or system limits being reached. In this case, users may have great-looking, fast reports that do not provide value due to the data being stale.

The author of this book has experienced the effects of poor report performance firsthand. In one project, a large utility company underwent a large migration from one reporting platform to another, from a different vendor. Even though the new platform was technically and functionally superior, the developers tried to copy the old reporting functionality across exactly. This led to poor design choices and very slow report performance. Millions of dollars in licensing and consulting fees were spent, yet most users refused to adopt the new system because it slowed them down so much. While it is extreme, this example demonstrates the potential ramifications when you do not build good performance into an analytical solution.

In this chapter, you will begin your journey to achieving good and consistent performance in Microsoft Power BI. To introduce the full scope of performance management, we will describe a Power BI solution as a stream of data from multiple sources being consolidated and presented to data analysts and information workers. We look at how data can be stored in Power BI and the different paths it can take before reaching a user. Many of the initial architectural design choices made in the early stages of the solution are very difficult and costly to change later. Hence, it is important to have a solid grasp of the implications of these choices and use a data-driven approach to help us decide what is best right at the start.

An area of performance management that is easily overlooked is that of setting performance targets. How do you know whether the experience you are delivering is great, merely acceptable, or poor? We will begin by exploring this theoretical area first to define our goals before diving into technical concepts.

This chapter is broken into the following sections:

  • Defining good performance
  • Considering areas that can slow you down
  • Which choices affect performance?