English | 2023 | ISBN: 978-1837634453 | 324 Pages | PDF, EPUB | 60 MB
Discover how Snowflake’s unique objects and features can be used to leverage universal modeling techniques through real-world examples and SQL recipes
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
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 features and applications of data modeling
- Explore Snowflake’s cloud-native architecture and features
- Understand and apply modeling concepts, techniques, and language using Snowflake objects
- Master modeling concepts such as normalization and slowly changing dimensions
- Get comfortable reading and transforming semi-structured data
- Work directly with pre-built recipes and examples
- Apply modeling frameworks from Star to Data Vault
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