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

Getting the facts straight

The facts in a source system are recorded in real time and updated in case of adjustments. By definition, they are always current. A DWH has a much harder task because it needs to capture and report current facts and track historical changes. Suppose an order was adjusted from containing two items to one. The DWH must find a way to report that a change was made while avoiding the issue of double-counting (as the total quantity is now one, not three).

The task of historical tracking is made even more complicated when the facts are not point-in-time transactions but intervals such as advertising campaigns or employee hires and leavers. In such cases, tabulating the cost of a department can no longer be accomplished by simple aggregation because employees can come and go at various intervals.

Operating a business is messy and complex, and the data that it generates is no exception. Employees come and go, orders are returned, and in some cases, records...