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

Speaking Modeling through Snowflake Objects

In its purest form, relational modeling (normalized tables with strictly enforced physical constraints) is most often found in online transaction processing (OLTP) databases. Transactional databases store the latest (as-is) version of business information, unlike data warehouses, which store historical snapshots and track changes in the information over time, allowing for additional (as-at) analysis across a temporal dimension.

However, this does not mean that relational modeling concepts do not apply in an online analytical processing (OLAP) database—quite the contrary. A data warehouse not only replicates existing entities and relations from transactional systems but also needs to manage the added task of conforming dimensions from other sources and joining them together in downstream transformations and analyses.

Another reason to master the common language of modeling is the Hybrid Unistore tables described in the previous...