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

Product type Paperback

Published in May 2023

Publisher Packt

ISBN-13 9781837634453

Length 324 pages

Edition 1st Edition

Languages

SQL

Tools

Snowflake

Concepts

Data Engineering

Author (1):

Serge Gershkovich

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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 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

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Appendix

Adding attributes

The most important detail in a dimension is its unique identifier. This determines what constitutes a unique instance of each entity in our business. Examples of unique identifiers include things such as serial numbers for parts and employee IDs for a company’s human capital. Domain experts from each business area can confirm these and other necessary details. We will use the CUSTOMER dimension as an example to identify the relevant details and incorporate them into the model.

Suppose we sat down with the head of the sales team to learn about how our organization identifies customers and their relevant attributes. The domain expert explains that besides typical customer attributes such as name and address, our organization is also interested in tracking the account balance and identifying its market segment. The sales team also explains how customers are grouped into regions based on their NATION attribute, maintained in a separate LOCATION dimension. Besides...