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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 data modeling techniques

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Product type Paperback
Published in May 2023
Publisher Packt
ISBN-13 9781837634453
Length 324 pages
Edition 1st 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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Table of Contents (24) Chapters Close

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

Embarking on conceptual design

Out of all the modeling types, conceptual captures and displays the least amount of detail. This makes conceptual modeling ideal for getting acquainted with a database landscape at a high level and for designing one from scratch. Designing data models is an art honed over many iterations, but where do you begin if you are new to modeling?

Dimensional modeling

In the early 2000s, Ralph Kimball and Margy Ross published the groundbreaking book The Data Warehouse Toolkit, which has persisted for decades as the authoritative blueprint for constructing database designs. Many of the terms, concepts, and techniques described in later chapters of this book trace their origins to The Data Warehouse Toolkit—whose latest edition fittingly carries the subtitle, The definitive guide to dimensional modeling.

To be clear, Kimball’s approach is not the only way to go about creating a conceptual model. The agile-based Business Event Analysis and...

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