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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 (28 chapters)
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1
Core Concepts in Data Modeling and Snowflake Architecture
9
Applied Modeling from Idea to Deployment
15
Solving Real-World Problems with Transformational Modeling
21
Data Modeling for Enterprise Teams
23
Unlocking Value for Enterprise Organizations
25
Other Books You May Enjoy
26
Index

Summary

While a physical model reflects the company’s business model, transformational models typically focus on addressing analytical business questions. Transformational models depend on existing data to perform their functions and, since data grows and changes over time, the object type used to represent the underlying logic may also change. By keeping object names constant, users can make adjustments and pivot between different database objects without breaking downstream processes.

The relationships established in the physical models can inform transformational designs as well as improving performance through join elimination by using the RELY property. Users can track performance to spot potential query issues using the query profile in the Snowflake UI. The query profile is a valuable tool for identifying performance issues such as exploding joins and inefficient pruning.

While transformational modeling is performed on top of the physical model, the two should...

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