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

Scaling with composite models and aggregations

So far, we have discussed how Import mode offers the best possible speed for Power BI datasets. However, sometimes, high data volumes and their associated refresh limitations may lead you to select DirectQuery mode instead. At this point, you may want to review the Choosing between Import and DirectQuery mode section on choosing a storage mode in Chapter 2, Exploring Power BI Architecture and Configuration, to remind yourself about the differences and rationale for choosing one over the other.

We also discussed how the Analysis Services engine is designed to aggregate data efficiently because BI solutions typically aggregate data most of the time. When we use DirectQuery, we want to push these aggregations down to the source where possible to avoid Power BI having to bring all the data over to compute them. With very large tables containing tens of millions to billions of rows, these aggregations can be costly and time-consuming, even...