Search icon
Arrow left icon
All Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Newsletters
Free Learning
Arrow right icon
Mastering Microsoft Power BI – Second Edition - Second Edition

You're reading from  Mastering Microsoft Power BI – Second Edition - Second Edition

Product type Book
Published in Jun 2022
Publisher Packt
ISBN-13 9781801811484
Pages 712 pages
Edition 2nd Edition
Languages
Authors (2):
Gregory Deckler Gregory Deckler
Profile icon Gregory Deckler
Brett Powell Brett Powell
Profile icon Brett Powell
View More author details

Table of Contents (18) Chapters

Preface 1. Planning Power BI Projects 2. Preparing Data Sources 3. Connecting to Sources and Transforming Data with M 4. Designing Import, DirectQuery, and Composite Data Models 5. Developing DAX Measures and Security Roles 6. Planning Power BI Reports 7. Creating and Formatting Visualizations 8. Applying Advanced Analytics 9. Designing Dashboards 10. Managing Workspaces and Content 11. Managing the On-Premises Data Gateway 12. Deploying Paginated Reports 13. Creating Power BI Apps and Content Distribution 14. Administering Power BI for an Organization 15. Building Enterprise BI with Power BI Premium 16. Other Books You May Enjoy
17. Index

Performance testing

Given that DAX measures can implement complex business logic and are dynamically calculated as users interact with reports, the performance of these calculations is a critical component of providing a good user experience.

There are often many available methods of implementing business logic and custom filter contexts into DAX measures. Although these alternatives deliver the essential functional requirements, they can have very different performance characteristics, which can ultimately impact user experience and the scalability of a dataset.

When migrating a self-service dataset to a corporate solution or preparing a large and highly utilized dataset, it’s always a good practice to test common queries and the DAX measures used by those queries.

For example, the same common dimension grouping (for example, Product Category and Year) and the same filter context (Year = 2018) could produce dramatically different performance results based on the...

lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at €14.99/month. Cancel anytime}