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Microsoft Power BI Performance Best Practices
Bhavik Merchant, Christopher Webb
- 312 pages
- English
- ePUB (adapté aux mobiles)
- Disponible sur iOS et Android
Microsoft Power BI Performance Best Practices
Bhavik Merchant, Christopher Webb
Ă propos de ce livre
Supercharge performance analytics and create repeatable patterns to ensure you get the best performance and scalability from your analytics solutions with Power BIKey Featuresâą Learn how to build performant data models and apply Row-Level Securityâą Identify and fix performance issues in reports, DAX, and datasets using DAX Studio/VertiPaq Analyzerâą Use a formal process to manage performance, from setting targets to monitoring and remediating issuesBook DescriptionThis 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.What you will learnâą Understand how to set realistic performance targets and address performance proactivelyâą Understand how architectural options and configuration affect performanceâą Build efficient Power BI reports and data transformationsâą Explore best practices for data modeling, DAX, and large datasetsâą Understand the inner workings of Power BI Premiumâą Explore options for extreme scale with Azure servicesâą Understand how to use tools that help identify and fix performance issuesWho this book is forData analysts, BI developers, and data professionals who have learnt the basics of Power BI and now want to understand how to build advanced analytics solutions will find this business intelligence book useful. Familiarity with the major components of Power BI and a beginner-level understanding of their purpose and use cases are required.
Foire aux questions
Informations
Part 1: Architecture, Bottlenecks, and Performance Targets
- Chapter 1, Setting Targets and Identifying Problem Areas
- Chapter 2, Exploring Power BI Architecture and Configuration
- Chapter 3, DirectQuery Optimization
Chapter 1: Setting Targets and Identifying Problem Areas
- Defining good performance
- Considering areas that can slow you down
- Which choices affect performance?
Defining good performance
Report performance goals
Setting realistic performance targets
Table des matiĂšres
- Microsoft Power BI Performance Best Practices
- Foreword
- Preface
- Part 1: Architecture, Bottlenecks, and Performance Targets
- Chapter 1: Setting Targets and Identifying Problem Areas
- Chapter 2: Exploring Power BI Architecture and Configuration
- Chapter 3: DirectQuery Optimization
- Part 2: Performance Analysis, Improvement, and Management
- Chapter 4: Analyzing Logs and Metrics
- Chapter 5: Desktop Performance Analyzer
- Chapter 6: Third-Party Utilities
- Chapter 7: Governing with a Performance Framework
- Part 3: Fetching, Transforming, and Visualizing Data
- Chapter 8: Loading, Transforming, and Refreshing Data
- Chapter 9: Report and Dashboard Design
- Part 4: Data Models, Calculations, and Large Datasets
- Chapter 10: Data Modeling and Row-Level Security
- Chapter 11: Improving DAX
- Chapter 12: High-Scale Patterns
- Part 5: Optimizing Premium and Embedded Capacities
- Chapter 13: Optimizing Premium and Embedded Capacities
- Chapter 14: Embedding in Applications
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