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

Cementing the relationships

With attributes and PK and FK relationships established in the dimensions, we again turn to the business experts to help flesh out the fact tables and determine their grain.

Building from the conceptual model, we ensure that all relationships have a defined granularity and optionality and that the data teams understand their business context. Mistakes made in the fact table definition are the costliest to reconcile and could result in costly readjustment, so extra care should be taken. Work with domain experts to ensure that the fact tables capture the true atomic grain of the information recorded by business operations and that the optionality is correctly understood.

In the following example, the logistics team confirms that our warehouse separates parts by the supplier to facilitate returns and inventory tracking. In short, the warehouse can store many parts from many suppliers. Role names are also verified and documented at this point for non-obvious...