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

Discovering Data Mesh

Data Mesh (DM) is an approach to organizing and managing data in large, complex organizations, introduced in 2019 by Zhamak Dehghani, a thought leader in the field of data architecture.

The DM approach advocates for decentralized data ownership and governance, with data treated as a product owned and managed by the teams using it. This contrasts with the traditional centralized (or, as Zhamak calls it, monolithic) approach to data management, where a single team or department is responsible for all data-related activities.

In a DM architecture, data is organized into self-contained domains, each responsible for its own data curation and sharing. These domains are often organized around business capabilities or processes and are staffed by cross-functional teams that include technical and business experts.

DM consists of four principles that aim to enable effective communication and collaboration between domains: domain-driven design, self-service, and...