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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
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Data Modeling with Snowflake

Data Modeling with Snowflake

5 (0)
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

Putting Conceptual Modeling into Practice

Conceptual database modeling is a high-level approach to designing a database that focuses on capturing business entities and their relationships. This approach allows designers to develop a deeper understanding of the data, making it easier to identify potential issues or inconsistencies in the design. It can also make the database more flexible and adaptable to future changes and make it easier to understand and use for people who are unfamiliar with it. As a result, conceptual database modeling can help make a database more effective and efficient at supporting the needs of an organization.

In this chapter, we will generate a conceptual model from scratch using Kimball’s dimensional modeling (DM) technique. This approach brings the data team together with business experts to ensure that database designs reflect the reality of business processes from inception, thereby saving costly rework down the line.

However, conceptual models...

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