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  • Book Overview & Buying Data Modeling with Snowflake
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Data Modeling with Snowflake

Data Modeling with Snowflake - Second Edition

By : Serge Gershkovich
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Data Modeling with Snowflake

Data Modeling with Snowflake

By: Serge Gershkovich

Overview of this book

Struggling with rising Snowflake costs and constant tuning? Poorly aligned data models can lead to bloated expenses, inefficient queries, and time-consuming rework. Data Modeling with Snowflake helps you harness the Snowflake Data Cloud’s scalable, cloud-native architecture and expansive feature set to deliver data solutions faster than ever. This book introduces simple, practical data modeling frameworks that accelerate agile design and evolve alongside your projects from concept to code. Rooted in decades of proven database design principles, these frameworks are paired, for the first time, with Snowflake-native objects and real-world examples, offering a two-in-one crash course in theory and direct application. Through real-world examples designed to make learning easy, you’ll leverage Snowflake’s innovative features like Time Travel, Zero-Copy Cloning, and Change Data Capture (CDC) to create cost-efficient solutions. Whether you're just starting out or refining your architecture, this book will guide you in designing smarter, scaling faster, and cutting costs by aligning timeless modeling principles with the power of Snowflake. *Email sign-up and proof of purchase required
Table of Contents (27 chapters)
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1
Part 1: Core Concepts in Data Modeling and Snowflake Architecture
9
Part 2: Applied Modeling from Idea to Deployment
15
Part 3: Solving Real-World Problems with Transformational Modeling
21
Part 4: Data Modeling for Enterprise Teams
23
Unlocking Value for Enterprise Organizations
24
Other Books You May Enjoy
25
Index

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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