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Microsoft Power BI Cookbook

You're reading from   Microsoft Power BI Cookbook Convert raw data into business insights with updated techniques, use cases, and best practices

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Product type Paperback
Published in Jul 2024
Publisher Packt
ISBN-13 9781835464274
Length 598 pages
Edition 3rd 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
Author Profile Icon Brett Powell
Brett Powell
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Toc

Table of Contents (16) Chapters Close

Preface 1. Installing and Licensing Power BI Tools FREE CHAPTER 2. Accessing, Retrieving, and Transforming Data 3. Building a Power BI Semantic Model 4. Authoring Power BI Reports 5. Working in the Power BI Service 6. Getting Serious About Date Intelligence 7. Parameterizing Power BI Solutions 8. Implementing Dynamic User-Based Visibility in Power BI 9. Applying Advanced Analytics and Custom Visuals 10. Enhancing and Optimizing Existing Power BI Solutions 11. Deploying and Distributing Power BI Content 12. Integrating Power BI with Other Applications 13. Working with Premium and Microsoft Fabric 14. Other Books You May Enjoy
15. Index

Using DirectQuery

One of the most valuable features of Power BI is its deep support for real-time and streaming semantic models, with the ability to provide immediate visibility to business processes and events as this data is created or updated. As Power BI has become Microsoft’s flagship semantic modeling tool, with exclusive features not available in Azure Analysis Services or SQL Server Analysis Services, it has become feasible to design both DirectQuery models and composite models which utilize a mixture of DirectQuery and import storage modes on a per table basis.

The three most common candidates for DirectQuery or composite model projects are as follows:

  • The data model would consume an exorbitant amount of memory if all tables were fully loaded into memory. Even if the memory size is technically supported by large Power BI Premium capacity nodes, this would be a very inefficient and expensive use of company resources, as most BI queries only access aggregated...
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