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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

Fact table types

By capturing the daily operational transactions of an organization, fact tables tend to contain large amounts of records that are constantly growing. By analyzing the data in fact tables, analysts and business users glean insights into business performance and identify trends and patterns. Considering these demands, fact tables must be designed in such a way that balances data loading efficiency with analytical needs and query patterns.

After nearly 20 years and three editions, the definitive guide to designing fact tables remains The Data Warehouse Toolkit. In it, authors Ralph Kimball and Margy Ross expertly cover the fundamentals of dimensional modeling, fact table design, and related industry case studies. This chapter will not attempt to replicate the content to which Kimball and Ross have dedicated nearly a quarter of their book. Instead, we will focus on what The Data Warehouse Toolkit does not cover: database-specific transformations for managing and maintaining...

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Data Modeling with Snowflake
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