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

Tables

Data in Snowflake is stored in tables, which, as discussed, are one of the fundamental components of data modeling. However, before exploring them in a modeling context, we should understand the various table types that exist in Snowflake and their costs.

The previous chapter described Snowflake’s Time Travel, a feature that allows restoring dropped objects or querying data at a prior point in time. However, Time Travel comes with associated storage costs, and the number of available Time Travel days—known as the retention period—depends on the table type, as we’ll shortly review in detail.

Snowflake also offers a managed type of Time Travel, known as Fail-safe. All permanent tables have a Fail-safe period of seven days. Unlike Time Travel, which the user can access, Fail-safe is managed by and accessible only to Snowflake to protect user data from disasters such as system failures and data breaches. To recover data stored in Fail-safe, users...