Book Image

Data Modeling with Snowflake

By : Serge Gershkovich
5 (2)
Book Image

Data Modeling with Snowflake

5 (2)
By: Serge Gershkovich

Overview of this book

The Snowflake Data Cloud is one of the fastest-growing platforms for data warehousing and application workloads. Snowflake's scalable, cloud-native architecture and expansive set of features and objects enables you to deliver data solutions quicker than ever before. Yet, we must ensure that these solutions are developed using recommended design patterns and accompanied by documentation that’s easily accessible to everyone in the organization. This book will help you get familiar with simple and practical data modeling frameworks that accelerate agile design and evolve with the project from concept to code. These universal principles have helped guide database design for decades, and this book pairs them with unique Snowflake-native objects and examples like never before – giving you a two-for-one crash course in theory as well as direct application. By the end of this Snowflake book, you’ll have learned how to leverage Snowflake’s innovative features, such as time travel, zero-copy cloning, and change-data-capture, to create cost-effective, efficient designs through time-tested modeling principles that are easily digestible when coupled with real-world examples.
Table of Contents (24 chapters)
1
Part 1: Core Concepts in Data Modeling and Snowflake Architecture
8
Part 2: Applied Modeling from Idea to Deployment
14
Part 3: Solving Real-World Problems with Transformational Modeling

Data models on a spectrum of normalization

The prior sections demonstrate how, as we move up the normal form scale, redundancy and the potential for data anomalies decrease while raising the number of tables and associated complexity. With this in mind, we can visualize where various data modeling patterns fall on the normal form spectrum to help understand their suitability in design scenarios. While the dimensional modeling process was discussed in Chapter 7, Putting Conceptual Modeling into Practice, the associated schema patterns (star and snowflake) are explained in further detail in Chapter 17, Scaling Data Models through Modern Techniques, along with Data Vault (where they are often implemented at the information mart layer). However, visualizing them in the context of normal forms will help lay the groundwork for later understanding their design. Also, bear in mind that the following assertions speak to general tendencies, not hard-set rules.

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