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

Summary

In this chapter, we saw how naming standards and an organized structure make the database easier to use and facilitate maintenance. But every organization is different and must choose the standard that best suits their needs and aligns with existing conventions.

Internally, Snowflake stores object names as uppercase, and its query compiler converts all unquoted names accordingly. It is recommended to use snake case for naming and stick to an established pattern to maximize the results cache utilization and to avoid enclosing every column and table name in double quotes.

For a clean transition between logical and physical models, singular table names are encouraged. The same applies to columns, which should be named consistently across the entire database. Using descriptive naming patterns for foreign keys allows users to preserve logical relationship names within the physical model.

After object naming, the attention turns to database organization through logical schema...