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

Through various examples in this chapter, we saw how the process of normalization organizes a database in a way that reduces redundancy and dependency within its tables.

Dependency and redundancy in database tables increase the likelihood of data anomalies, which come in many forms. Update anomalies occur due to redundancy, which makes it possible to update some, but not all, of the associated records. Physical (as opposed to logical) dependencies are the root cause of insertion and deletion anomalies. When too many details of varying granularity are bunched into a single table, inserting or deleting records that do not match all the criteria becomes difficult. The domain anomaly is the hardest to spot because it requires functional knowledge of the data in question.

Database normalization can be applied through escalating stages of formal rules called normal forms, ranging from 1NF to 6NF to avoid such anomalies. The most commonly used normal forms are the first through...