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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
Languages
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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

Unlocking the Power of Modeling

The word modeling has come to mean very different things in the half a century that it has been practiced in database systems. This opening chapter prefaces the book’s overall aim to demystify modeling, along with its applications, methodologies, and benefits. Throughout this journey, the concept of modeling will unfold into a set of methods and terms that help organizations design and manage data and, more importantly, help them understand themselves.

In its broadest interpretation, modeling is a selective simplification that aids in navigating or designing something more complex. Any system can be broken down into smaller, more manageable pieces. Manipulating any piece individually may be straightforward, but doing so without regard to an overall strategy is a tenuous proposal that is sure to encumber scalability and maintenance down the line.

While modeling is generally considered database-agnostic, modern cloud data platforms, such as Snowflake, present their users with many unique features thanks to their innovative architecture and consumption-based pricing. A clear and forward-looking design that takes advantage of the native features of the platform that supports it is the key to building cost-effective solutions capable of meeting and anticipating business needs.

As the analytical requirements of a data-driven organization are notoriously complex and constantly evolving, modeling must keep pace and accompany data teams from idea to execution. To achieve this, modeling must go beyond the structure and relationships of database tables and embrace the transformational logic that moves and shapes the underlying data. Only by leaning into the specifics of Snowflake features and architecture can a model be built efficiently from beginning to end.

In this chapter, we’re going to cover the following main topics:

  • Recognizing the utility of models in our daily lives
  • Getting a glimpse of modeling conventions in action
  • Getting acquainted with the tools in the modeling toolkit
  • Uncovering the benefits of modeling for enterprise teams
  • Incorporating modeling into strategic planning
  • Understanding modeling applications for transactional and analytical systems
You have been reading a chapter from
Data Modeling with Snowflake
Published in: May 2023
Publisher: Packt
ISBN-13: 9781837634453
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