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Data Modeling with Snowflake

You're reading from   Data Modeling with Snowflake A practical guide to accelerating Snowflake development using universal modeling techniques

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Product type Paperback
Published in Sep 2025
Publisher Packt
ISBN-13 9781837028030
Length 432 pages
Edition 2nd Edition
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Author (1):
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Serge Gershkovich Serge Gershkovich
Author Profile Icon Serge Gershkovich
Serge Gershkovich
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Toc

Table of Contents (28) Chapters Close

Preface 1. Core Concepts in Data Modeling and Snowflake Architecture
2. Unlocking the Power of Modeling FREE CHAPTER 3. An Introduction to the Four Modeling Types 4. Mastering Snowflake’s Architecture 5. Mastering Basic Snowflake Objects 6. From Logical Concepts to Snowflake Objects 7. Mastering Advanced Snowflake Objects 8. Seeing Snowflake’s Architecture Through Modeling Notation 9. Applied Modeling from Idea to Deployment
10. Putting Conceptual Modeling into Practice 11. Putting Logical Modeling into Practice 12. Database Normalization 13. Database Naming and Structure 14. Putting Physical Modeling into Practice 15. Solving Real-World Problems with Transformational Modeling
16. Putting Transformational Modeling into Practice 17. Modeling Slowly Changing Dimensions 18. Modeling Facts for Rapid Analysis 19. Modeling Semi-Structured Data 20. Modeling Hierarchies 21. Data Modeling for Enterprise Teams
22. Scaling Data Models through Modern Techniques 23. Unlocking Value for Enterprise Organizations 24. Unlock Your Exclusive Benefits 25. Other Books You May Enjoy
26. Index
Appendix

Data models on a spectrum of normalization

The prior sections demonstrate how, as we move up the normal form scale, redundancy and the potential for data anomalies decrease while raising the number of tables and associated complexity. With this in mind, we can visualize where various data modeling patterns fall on the normal form spectrum to help understand their suitability in design scenarios. While the dimensional modeling process was discussed in Chapter 8, Putting Conceptual Modeling into Practice, the associated schema patterns (star and snowflake) are explained in further detail in Chapter 18, Scaling Data Models Through Modern Techniques, along with Data Vault (where they are often implemented at the information mart layer). However, visualizing them in the context of normal forms will help lay the groundwork for later understanding their design. Also, bear in mind that the following assertions speak to general tendencies, not hard-set rules.

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