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Mastering Microsoft Power BI – Second Edition

You're reading from   Mastering Microsoft Power BI – Second Edition Expert techniques to create interactive insights for effective data analytics and business intelligence

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Product type Paperback
Published in Jun 2022
Publisher Packt
ISBN-13 9781801811484
Length 712 pages
Edition 2nd Edition
Languages
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Authors (2):
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Greg Deckler Greg Deckler
Author Profile Icon Greg Deckler
Greg Deckler
Brett Powell Brett Powell
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Brett Powell
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Table of Contents (18) Chapters Close

Preface 1. Planning Power BI Projects 2. Preparing Data Sources FREE CHAPTER 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...

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