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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

Unlocking the Power of Modeling

The word modeling has come to mean very different things in the half a century that it has been practiced in database systems. This opening chapter prefaces the book’s overall aim to demystify modeling, along with its applications, methodologies, and benefits. Throughout this journey, the concept of modeling will unfold into a set of methods and terms that help organizations design and manage data and, more importantly, help them understand themselves.

In its broadest interpretation, modeling is a selective simplification that aids in navigating or designing something more complex. Any system can be broken down into smaller, more manageable pieces. Manipulating any piece individually may be straightforward, but doing so without regard to an overall strategy is a tenuous proposal that is sure to encumber scalability and maintenance down the line.

While modeling is generally considered database-agnostic, modern cloud data platforms, such as Snowflake, present their users with many unique features thanks to their innovative architecture and consumption-based pricing. A clear and forward-looking design that takes advantage of the native features of the platform that supports it is the key to building cost-effective solutions capable of meeting and anticipating business needs.

As the analytical requirements of a data-driven organization are notoriously complex and constantly evolving, modeling must keep pace and accompany data teams from idea to execution. To achieve this, modeling must go beyond the structure and relationships of database tables and embrace the transformational logic that moves and shapes the underlying data. Only by leaning into the specifics of Snowflake features and architecture can a model be built efficiently from beginning to end.

In this chapter, we’re going to cover the following main topics:

  • Recognizing the utility of models in our daily lives
  • Getting a glimpse of modeling conventions in action
  • Getting acquainted with the tools in the modeling toolkit
  • Uncovering the benefits of modeling for enterprise teams
  • Incorporating modeling into strategic planning
  • Understanding modeling applications for transactional and analytical systems
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Data Modeling with Snowflake
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