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Data Modeling with Snowflake

Data Modeling with Snowflake

By : Serge Gershkovich
4.6 (19)
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Data Modeling with Snowflake

Data Modeling with Snowflake

4.6 (19)
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)
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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

Appendix

Wouldn’t it be fitting if a book on modeling was itself modeled after something? Well, it has been! This book follows a spiral model, starting from a high-level overview of modeling and rising in winding loops, revisiting its core elements in ever-greater depth and complexity. This may seem like an unorthodox approach, but I believe that the difficulty of the technical how is alleviated by the understanding of the conceptual why. As such, I made it a point not to presuppose any modeling knowledge beyond a basic understanding of SQL and to never lean on a term or concept before formally introducing it.

Following a helical structure while writing this text allowed me to carve out a clear path from the theoretical to the technical and kept me from drifting into areas that were not core to the central theme. Inevitably, some exercises had to be excluded because they did not cleanly fit within the framework of the chapters. Rather than leave them on the proverbial cutting...

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Data Modeling with Snowflake
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