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

Building efficient data models

We will begin with some theoretical concepts on how to model data for fast query performance. These techniques were designed with usability in mind but happen to be the perfect way to model data for the Analysis Services engine in Power BI. We will begin by introducing star schemas because they are native to the Analysis Services engine and it is optimized to work with them.

The Kimball theory and implementing star schemas

Data modeling can be thought of as how to group and connect the attributes in a set of data. There are competing schools of thought as to what style of data modeling is the best and they are not always mutually exclusive. Learning about competing data modeling techniques is beyond the scope of this book.

We will be looking at dimensional modeling, a very popular technique that was established by the Kimball Group over 30 years ago. It is considered by many to be an excellent way to present data to business users and happens...