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

Putting transformational modeling into practice

In the last chapter, we deployed our sample physical model. Here, we will populate it with data and create a transformational model to satisfy a business requirement using the techniques and best practices covered in the preceding sections.

Transformational modeling requires data. The script to populate our operational schema with sample data can be found in the Git repository for this chapter. Please run the script titled create_physical_model_w_data.sql to recreate the physical model and load it with data from the SNOWFLAKE_SAMPLE_DATA database if you have not already done so.

After running the script, all the transactional tables in the schema will have been populated with data. However, the LOYALTY_CUSTOMER table is not transactional; it needs to be created through a transformational model. Just as the data model in the previous chapters took shape after getting to know the workings of our company by communicating with the business...