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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

Deploying a physical model

At this point, all the tables, relationships, and properties have been defined and are ready to be deployed to Snowflake. If you use a modeling tool, all the DDL will be generated behind the scenes as adjustments are made to the diagram through a process called forward engineering. While it’s not strictly necessary to use a modeling tool to forward engineer, doing so will make it easier to make adjustments and generate valid, neatly formatted SQL for your data model.

For those following the exercise, the forward-engineered DDL from this exercise is available in a shared Git repository mentioned at the start of this chapter.

With the DDL in hand, pay attention to the database and schema context in the Snowflake UI. Creating a database or schema will automatically set the context for a given session. To switch to an existing database or schema, use the context menu in the UI or the USE <object> <object name> SQL expression. Here’...

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