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

Understanding Premium services, resource usage, and Autoscale

Power BI Premium provides reserved capacity for your organization. This isolates you from the noisy-neighbor problem that you may experience in the shared capacity. Let's start by briefly reviewing the capabilities of the Premium capacities that differentiate it by providing greater performance and scale:

  • Ability to Autoscale: This is a new capability that was introduced in Gen2 that allows administrators to assign spare CPU cores to be used in periods of excessive load (not available for PPU).
  • Higher Storage and Dataset Size Limits: 100 TB of total storage and a 400 GB dataset size (100 GB in PPU).
  • More Frequent Dataset Refresh: 48 times per day via the UI and potentially more via scripting through the XMLA endpoint.
  • Greater Refresh Parallelism: You can have more refreshes running at the same time, ranging from 5 (Embedded A1) to 640 (Premium P5/Embedded A8).
  • Advanced Dataflows Features: Premium...