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 13: Optimizing Premium and Embedded Capacities

In the previous chapter, we looked at ways to deal with high data and user scale. The first option we provided was to leverage Power BI Premium because it has higher dataset size limits than Power BI's shared capacity.

In this chapter, we will take a much closer look at the Premium (P and EM) and Embedded (A) capacities. Even though they are purchased and billed differently, with a couple of minor exceptions, they offer the same services on similar hardware and benefit from the same optimization guidance. Therefore, we will continue to refer to just the Premium capacity for the remainder of this chapter and will call out Embedded only if there is a material difference. We will treat the Premium Per User (PPU) licensing model the same way.

We will learn how there is more to differentiate Premium than just the increased dataset limits. This is because the Premium capacity offers unique services and advanced features...