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Microsoft Power BI Performance Best Practices

You're reading from Microsoft Power BI Performance Best Practices Learn practical techniques for building high-speed Power BI solutions

Product type Paperback

Published in Aug 2024

Publisher Packt

ISBN-13 9781835082256

Length 346 pages

Edition 2nd Edition

Languages

DAX

Tools

Azure

Concepts

Business Intelligence

Authors (2):

Thomas LeBlanc

Bhavik Merchant

View More author details

Table of Contents (23) Chapters

Preface

1. Part 1: Architecture, Bottlenecks, and Performance Targets

2. Chapter 1: Setting Targets and Identifying Problem Areas FREE CHAPTER

3. Chapter 2: Exploring Power BI Architecture and Configuration

4. Chapter 3: Learning the Tools for Performance Tuning

5. Part 2: Performance Analysis, Improvement, and Management

6. Chapter 4: Analyzing Logs and Metrics

7. Chapter 5: Optimization for Storage Modes

8. Chapter 6: Third-Party Utilities

9. Chapter 7: Performance Governance Framework

10. Part 3: Fetching, Transforming, and Visualizing Data

11. Chapter 8: Loading, Transforming, and Refreshing Data

12. Chapter 9: Report and Dashboard Design

13. Part 4: Data Models, Calculations, and Large Semantic Models

14. Chapter 10: Dimensional Modeling and Row Level Security

15. Chapter 11: Improving DAX

16. Chapter 12: High Scale Patterns

17. Part 5: Optimizing Capacities in Power BI Enterprises

18. Chapter 13: Working with Capacities

19. Chapter 14: Performance Needs for Fabric Artifacts

20. Chapter 15: Embedding in Web Apps

21. Index

Why subscribe?

22. Other Books You May Enjoy

Index

As this ebook edition doesn't have fixed pagination, the page numbers below are hyperlinked for reference only, based on the printed edition of this book.

Symbols

Globally Unique Identifier (GUID) 199

A

Aggregations feature 20

AI functions 261

Analysis Service 36

Analysis Services server traces

with XMLA endpoint 76

Application Life Cycle Management (ALM) 259

attribute 99

Autoscale

used, for handling peak loads in Premium capacity 267-269

Azure Analysis Services (AAS)

Azure diagnostics 78

Azure metrics 77, 78

monitoring 77

using, for data and user scale 234, 235

Azure Analysis Services (AAS), monitoring

reference link 77

Azure Data Factory (ADF) 288

Azure Data Lake Storage Gen2 (ADLS) 248

Azure Data Pipelines 288

Azure Log Analytics

integration with 77

reference link 77

Azure metrics and diagnostics

for Power BI Embedded (PBIE) 79

Azure Synapse Analytics and Fabric 249,...

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Authors (2)

Thomas LeBlanc

Thomas LeBlanc

Thomas LeBlanc is a seasoned Business Intelligence Architect at Data on the Geaux, where he applies his extensive skillset in dimensional modeling, data visualization, and analytical modeling to deliver robust solutions. With a Bachelor of Science in Management Information Systems from Louisiana State University, Thomas has amassed over 30 years of experience in Information Technology, transitioning from roles as a software developer and database administrator to his current expertise in business intelligence and data warehouse architecture and management. Throughout his career, Thomas has spearheaded numerous impactful projects, including consulting for various companies on Power BI implementation, serving as lead database administrator for a major home health care company, and overseeing the implementation of Power BI and Analysis Service for a large bank. He has also contributed his insights as an author to the Power BI MVP book. Thomas is recognized as a Microsoft Data Platform MVP and is actively engaged in the tech community through his social media presence, notably as TheSmilinDBA on Twitter and ThePowerBIDude on Bluesky and Mastodon. With a passion for solving real-world business challenges with technology, Thomas continues to drive innovation in the field of business intelligence.

See other products by Thomas LeBlanc

Bhavik Merchant

Bhavik Merchant

Bhavik Merchant has nearly 18 years of deep experience in Business Intelligence. He is currently the Director of Product Analytics at Salesforce. Prior to that, he was at Microsoft, first as a Cloud Solution Architect and then as a Product Manager in the Power BI Engineering team. At Power BI, he led the customer-facing insights program, being responsible for the strategy and technical framework to deliver system-wide usage and performance insights to customers. Before Microsoft, Bhavik spent years managing high-caliber consulting teams delivering enterprise-scale BI projects. He has provided extensive technical and theoretical BI training over the years, including expert Power BI performance training he developed for top Microsoft Partners globally.

See other products by Bhavik Merchant

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