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Data Modeling with Snowflake

You're reading from  Data Modeling with Snowflake

Product type Book
Published in May 2023
Publisher Packt
ISBN-13 9781837634453
Pages 324 pages
Edition 1st Edition
Languages
Author (1):
Serge Gershkovich Serge Gershkovich
Profile icon Serge Gershkovich

Table of Contents (24) Chapters

Preface 1. Part 1: Core Concepts in Data Modeling and Snowflake Architecture
2. Chapter 1: Unlocking the Power of Modeling 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

The secret column type Snowflake refuses to document

Snowflake’s co-founders and chief architects, Benoit Dageville and Thierry Cruanes, spent many years working at Oracle. In fact, Oracle’s influence can be seen in many of the SQL constructs and functions that Snowflake supports. One such example is the concept of the virtual column.

Virtual columns straddle the line between physical and transformational modeling—between table and view. Virtual columns look like normal table columns, but their values are derived rather than stored on disc. They are an efficient way to embed simple business rules and transformational logic in a table without the overhead of maintaining views and incurring storage costs. Virtual columns can be defined through constants or transformational expressions such as the DEFAULT column operator. Strangely, they are not mentioned in the CREATE TABLE documentation at the time of writing (https://docs.snowflake.com/en/sql-reference/sql/create...

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