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  • Book Overview & Buying Data Modeling with Snowflake
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Data Modeling with Snowflake

Data Modeling with Snowflake

By : Serge Gershkovich
4.6 (19)
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Data Modeling with Snowflake

Data Modeling with Snowflake

4.6 (19)
By: Serge Gershkovich

Overview of this book

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.
Table of Contents (24 chapters)
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1
Part 1: Core Concepts in Data Modeling and Snowflake Architecture
8
Part 2: Applied Modeling from Idea to Deployment
14
Part 3: Solving Real-World Problems with Transformational Modeling

Modeling Hierarchies

In the previous chapter, we learned about the methods and techniques for exploring semi-structured data in Snowflake. While not everyone works with operational web or app data such as JSON, there is another type of (semi-)structured data that exists across all organizations: hierarchies. Every company operates with hierarchical entities such as org levels (tiers of management and the reporting relationships between managers and employees) or calendar dimensions (rollups of days, months, fiscal periods, and years).

Whether formally maintained or naturally occurring, hierarchies are used within an organization to organize entities into meaningful groups and subgroups to facilitate rollups or drill-downs in data analysis. Besides aiding in the analysis of facts, hierarchies themselves can be examined to help organizations understand how they are structured, how they function, and how they can improve their performance by eliminating operational bottlenecks.

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