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

Mastering Snowflake’s Architecture

For as long as databases have existed, they have faced recurring challenges in managing concurrency and scalability in the face of growing data volume and processing demands. Many innovative designs have been attempted over the years and have been met with varying degrees of success. However, that success often came with fresh drawbacks.

The Snowflake team saw that overcoming the age-old challenges of handling independent consumption demands of data storage and analysis required a radically new approach. The team decided to design a database that could operate natively on top of cloud computing platforms and thereby offer near-limitless scalability. Their efforts resulted in the creation of what Snowflake calls the Data Cloud—a platform that enables real-time data sharing and on-demand workload sizing through the separation of storage and compute.

In this chapter, we will cover the following topics:

  • Explore how databases...