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

Attributes as columns

Recall from the previous section that an entity is a business-relevant concept for which an organization wishes to maintain information. Recall that attributes—defined with the business team during conceptual modeling or loaded from existing source data during the ETL process—are properties that describe the entity and are stored as columns. Attributes can be descriptive (such as NAME, ADDRESS, and QUANTITY) or metadata (such as ETL_SOURCE and LOAD_DATE).

The nature of the attribute—whether numeric, string, date, or other—is an essential detail for understanding the business requirement at the conceptual level and selecting the right data type at the physical level. Snowflake offers basic data types found in other databases (such as VARCHAR, DATE, and INTEGER) and less-common ones (such as VARIANT and GEOGRAPHY), which offer exciting possibilities for modeling and working with table contents.

Let us get to know Snowflake data...