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

A history of relational modeling

The diagrams and examples throughout this book rely on relational modeling to illustrate database concepts and constructs. Learning how to parse and communicate through relational diagrams provides a dual-faceted benefit to database users by allowing them to rapidly visualize and bring to life complex database landscapes and design them from scratch using visual cognitive aids. Yet, despite these benefits, many database users consider modeling an arcane practice without relevance in the modern warehouse and mistake it for a chore instead of the time-saving boon it really is.

The practice of data modeling and its associated notations have passed through many changes and diverging trends without a final standard ever emerging, encumbering universal adoption. The conceptual data model dates back to the 1960s when Charles Bachman first used rectangles to denote record types and arrows to form relationships between them. Toward the end of the decade,...