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

The secret column type Snowflake refuses to document

Snowflake’s co-founders and chief architects, Benoit Dageville and Thierry Cruanes, spent many years working at Oracle. In fact, Oracle’s influence can be seen in many of the SQL constructs and functions that Snowflake supports. One such example is the concept of the virtual column.

Virtual columns straddle the line between physical and transformational modeling—between table and view. Virtual columns look like normal table columns, but their values are derived rather than stored on disc. They are an efficient way to embed simple business rules and transformational logic in a table without the overhead of maintaining views and incurring storage costs. Virtual columns can be defined through constants or transformational expressions such as the DEFAULT column operator. Strangely, they are not mentioned in the CREATE TABLE documentation at the time of writing (https://docs.snowflake.com/en/sql-reference/sql/create...