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

Optimizing dataflows

A Power BI Dataflow is a type of artifact contained within a Power BI workspace. A dataflow contains Power Query data transformation logic, which is also defined in the M query language that we introduced earlier. The dataflow contains the definition of one or more tables produced by those data transformations. Once it has been successfully refreshed, the dataflow also contains a copy of the transformed data stored in Azure Data Lake.

A dataflow might seem very similar to the query objects you define in Power BI Desktop, and this is true. However, there are some important differences, as noted in the following points:

  • A dataflow can only be created online through the Power BI web application via Power Query Online.
  • A dataflow is a standalone artifact that can exist independently. It is not bundled or published with a dataset, but dataset items can use the dataflow as a standard data source.
  • There are some UI and functionality differences between...