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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
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23
Unlocking Value for Enterprise Organizations
24
Other Books You May Enjoy
25
Index

Data Modeling for Enterprise Teams

This part covers the emerging trends and leading methodologies in data modeling to meet the demands of the modern data-driven enterprise. Here, we review the basics of Data Vault methodology for building agile, scalable, and auditable architectures, and Data Mesh, which is becoming an increasingly popular approach to managing data domains at scale across large organizations. We also cover the data lakehouse approach for working with semi-structured and unstructured data and explore the topic of AI and the role data modeling plays in ensuring success in machine learning and inference training initiatives. Most importantly, we’ll learn to speak the language of the business and learn to defend data modeling using financial and value-based metrics. Finally, you will experiment hands-on with fun and effective SQL recipes that couldn’t be included in the rest of the chapters.

This part has the following chapters:

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83
Tech Concepts
36
Programming languages
73
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Data Modeling with Snowflake
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