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

Recipes for maintaining SCDs in Snowflake

Understanding the structure of an SCD and being able to load it correctly are very different concepts. With a firm grasp of SCD types, we will now cook up the recipes for creating and maintaining them in Snowflake. Unlike generic SQL techniques you may have used in other databases, this book will take full advantage of the cost- and time-saving capabilities of Snowflake’s core features, such as streams and zero-copy cloning.

Setting the stage

To give readers complete autonomy to construct, experiment, and modify the upcoming exercises, we will first create a base table that will simulate the day one snapshot of the data warehouse raw/source schema. The base table will represent the initial first load of the source data into the data warehouse. Next, we construct a routine that simulates a daily load of new and changed records.

For consistency with the first half of this chapter, these examples will use the CUSTOMER table from...