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

Part 2: Applied Modeling from Idea to Deployment

This part focuses on the practical application of data modeling techniques across different stages of the database design process. You will learn how to put conceptual modeling into practice by gaining a solid understanding of the data entities, relationships, and business rules that define the underlying data structure. You will also learn how to enrich these details and add nuance using a logical model that cannot be captured in a physical database. This part also delves into the critical concept of database normalization, essential for minimizing data redundancy and ensuring accurate and consistent data storage. After covering database naming and structure and exploring the best practices for creating intuitive, meaningful, and scalable database schemas, you will learn how to put physical modeling into practice while optimizing database performance.

This part has the following chapters: