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 12: High-Scale Patterns

In the previous chapter, we learned how to optimize DAX expressions. Having reached this point, we have rounded up all the advice on optimizing different layers of a Power BI solution, from the dataset layer to report design. In this chapter, we will take a step back and revisit architectural concepts and related features that help deal with very high data volumes.

The amount of data that organizations collect and need to analyze is increasing all the time. With the advent of the Internet of Things (IoT) and predictive analytics, certain industries, such as energy and resources, are collecting more data than ever. It is common for a modern mine or gas plant to have tens of thousands of sensors, each generating many data points at granularities much higher than a second.

Even with Power BI's data compression technology, it isn't always possible to load and store massive amounts of data in an Import mode model in a reasonable amount of...