Data Modeling with Snowflake: A practical guide to accelerating Snowflake development using universal data modeling techniques 259777

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259777
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Leverage the agility of universal modeling techniques through real-world examples and SQL templates using Snowflake's unique objects and features
Key Features
  • Learn core modeling techniques tied to practical examples using native Snowflake architecture
  • Adopt a universal modeling language to communicate business value to functional teams
  • Go beyond physical modeling with SQL recipes to transform and shape your Snowflake data
Book Description
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.
What you will learn
  • Discover the time-saving benefits and applications of data modeling
  • Learn about Snowflake's cloud-native architecture and its features
  • Understand and apply modeling techniques using Snowflake objects
  • Universal modeling concepts and language through Snowflake objects
  • Get comfortable reading and transforming semistructured data
  • Learn directly with pre-built recipes and examples
  • Learn to apply modeling frameworks from Star to Data Vault
Who this book is for
This book is for developers working with SQL who are looking to build a strong foundation in modeling best practices and gain an understanding of where they can be effectively applied to save time and effort. Whether you're an ace in SQL logic or starting out in database design, this book will equip you with the practical foundations of data modeling to guide you on your data journey with Snowflake. Developers who've recently discovered Snowflake will be able to uncover its core features and learn to incorporate them into universal modeling frameworks.
About the Author
Serge Gershkovich is a seasoned data architect with decades of experience designing and maintaining enterprise-scale data warehouse platforms and reporting solutions. He is a leading subject matter expert, speaker, content creator, and Snowflake Data Superhero. Serge earned a bachelor of science degree in information systems from the State University of New York (SUNY) Stony Brook. Throughout his career, Serge has worked in model-driven development from SAP BW/HANA to dashboard design to cost-effective cloud analytics with Snowflake. He currently serves as product success lead at SqlDBM, an online database modeling tool

Зміст

Table of Contents
  1. Unlocking the Power of Modeling
  2. An Introduction to the Four Modeling Types
  3. Mastering Snowflake's Architecture
  4. Mastering Snowflake Objects
  5. Speaking Modeling through Snowflake Objects
  6. Seeing Snowflake's Architecture through Modeling Notation
  7. Putting Conceptual Modeling into Practice
  8. Putting Logical Modeling into Practice
  9. Database Normalization
  10. Database Naming and Structure
  11. Putting Physical Modeling into Practice
  12. Putting Transformational Modeling into Practice
  13. Modeling Slowly Changing Dimensions
  14. Modeling Facts for Rapid Analysis
  15. Modeling Semi-Structured Data
  16. Modeling Hierarchies
  17. Scaling Data Models through Modern Techniques
  18. Appendix

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