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

Snowflake’s solution

To address the scalability issue that has plagued databases since inception, the Snowflake team decided to formulate a new approach that would not be tied down by the limitations of past designs. They developed a modern platform built natively for the cloud that uses its unique features to enable concurrency, scalability, and real-time collaboration.

Snowflake’s innovative cloud architecture still relies on physical disks, but it integrates them logically to make centralized storage available to its computing clusters without concurrency bottlenecks or data replication overhead. Finally, the best of what shared-disk and shared-nothing promised: separating the data from compute workloads, which can be independently provisioned and resized.

Snowflake runs entirely on virtually provisioned resources from cloud platforms (Amazon, Microsoft, and Google Cloud). Snowflake handles all interactions with the cloud provider transparently, abstracting the...