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Data Modeling with Snowflake
Data Modeling with Snowflake

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

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Profile Icon Serge Gershkovich
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Can$44.99 Can$50.99
Full star icon Full star icon Full star icon Full star icon Half star icon 4.8 (19 Ratings)
eBook May 2023 324 pages 1st Edition
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Arrow left icon
Profile Icon Serge Gershkovich
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Can$44.99 Can$50.99
Full star icon Full star icon Full star icon Full star icon Half star icon 4.8 (19 Ratings)
eBook May 2023 324 pages 1st Edition
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Can$63.99
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Data Modeling with Snowflake

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

Technical requirements

This book focuses on data modeling specifically for the Snowflake Data Cloud. While modeling includes many system-agnostic terms and conventions, this book will leverage unique features of Snowflake architecture, data types, and functions when building physical models and Structured Query Language (SQL) transformations.

To follow along with the exercises in the following chapters, you will need a Snowflake account with access to a sandbox area for creating schemas, objects, and loading data.

You can sign up for a 30-day free trial of Snowflake (https://signup.snowflake.com/) if you do not already have access.

This book will frequently use visual modeling diagrams as part of the modeling process. While a diagram can be drawn by hand and constructed in PowerPoint or Lucidchart, a tool that supports common database modeling features is recommended. The exercises in this book will take the reader from conceptual database-agnostic diagrams to deployable and runnable Snowflake code. For this reason, a tool that supports various modeling types and can forward engineer Snowflake syntax is recommended.

The diagrams in this book were generated using the SqlDBM online database modeling tool (https://sqldbm.com/Home/), which supports the previously mentioned features and offers a 2-week free trial.

Modeling with purpose

Models are used to simplify complex systems. Take a modern city as an example, and you will see that it consists of intricately linked systems such as highways, electrical grids, and transit systems. While these systems operate in the same physical territory, they require very different models to help us understand them. For example, a subway system snakes and curves below a city’s varied terrain, but our model of it—a subway map—uses straight lines and places stations at nearly equidistant intervals. The subway map is not the city—it is a selective simplification of the city that makes it easier for passengers to visualize their journey. The transit map is a model so ubiquitous that it’s hard to imagine doing it any other way—yet it took time to evolve.

The subway map, as we know it today, was invented by Harry Beck in 1931 while re-designing the map used by the London Underground. The old design was confusing to riders because it focused on the wrong goal—geographical exactness. Here’s what it looked like before Beck:

Figure 1.1 – London tube map, before Beck (Legacy Tube map)

Figure 1.1 – London tube map, before Beck (Legacy Tube map)

Thankfully, Beck was not a cartographer—he was an engineer. By sacrificing topographical detail, Beck’s design allowed passengers to quickly count the number of stops required for their journey while retaining their overall sense of direction. This story reminds us (quite literally) of the refrain, the map is not the territory.

As with maps, various kinds of modeling exist to help teams within an organization make sense of the many layers that make up its operational landscape. Also, like maps, models help organizations prepare for the journey ahead. But how does one use a model to navigate a database, let alone plan its future?

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Key benefits

  • 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

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.

Who is this book 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.

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

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Length: 324 pages
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Language : English
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Publication date : May 31, 2023
Length: 324 pages
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Table of Contents

22 Chapters
Part 1: Core Concepts in Data Modeling and Snowflake Architecture Chevron down icon Chevron up icon
Chapter 1: Unlocking the Power of Modeling Chevron down icon Chevron up icon
Chapter 2: An Introduction to the Four Modeling Types Chevron down icon Chevron up icon
Chapter 3: Mastering Snowflake’s Architecture Chevron down icon Chevron up icon
Chapter 4: Mastering Snowflake Objects Chevron down icon Chevron up icon
Chapter 5: Speaking Modeling through Snowflake Objects Chevron down icon Chevron up icon
Chapter 6: Seeing Snowflake’s Architecture through Modeling Notation Chevron down icon Chevron up icon
Part 2: Applied Modeling from Idea to Deployment Chevron down icon Chevron up icon
Chapter 7: Putting Conceptual Modeling into Practice Chevron down icon Chevron up icon
Chapter 8: Putting Logical Modeling into Practice Chevron down icon Chevron up icon
Chapter 9: Database Normalization Chevron down icon Chevron up icon
Chapter 10: Database Naming and Structure Chevron down icon Chevron up icon
Chapter 11: Putting Physical Modeling into Practice Chevron down icon Chevron up icon
Part 3: Solving Real-World Problems with Transformational Modeling Chevron down icon Chevron up icon
Chapter 12: Putting Transformational Modeling into Practice Chevron down icon Chevron up icon
Chapter 13: Modeling Slowly Changing Dimensions Chevron down icon Chevron up icon
Chapter 14: Modeling Facts for Rapid Analysis Chevron down icon Chevron up icon
Chapter 15: Modeling Semi-Structured Data Chevron down icon Chevron up icon
Chapter 16: Modeling Hierarchies Chevron down icon Chevron up icon
Chapter 17: Scaling Data Models through Modern Techniques Chevron down icon Chevron up icon
Index Chevron down icon Chevron up icon
Other Books You May Enjoy Chevron down icon Chevron up icon

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Utkarsh DIXIT Feb 13, 2024
Full star icon Full star icon Full star icon Full star icon Full star icon 5
I haven't read it yet . But will surely like it
Feefo Verified review Feefo
Ed Jul 18, 2023
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Took me three days to read it. Super informative and helpful.
Amazon Verified review Amazon
Amazon Customer Jul 17, 2023
Full star icon Full star icon Full star icon Full star icon Full star icon 5
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kashif Aug 21, 2023
Full star icon Full star icon Full star icon Full star icon Full star icon 5
The book is very comprehensive and takes you through step by step, It depends on where you like to start if you fall in beginner category then go from first chapter/ intermediate then start from chapter 7, Even through I feel it first edition is for beginner/intermediate level people but I would still say anyone can pick it and give a read. i haven't seen any book coming close to this book anywhereIt definitely emphasis the best recipes, these recipes can be still applied in other modern DWH.I would rate it 4.5 and encourage everyone to go for it, Even through it doesn't build complex modules and break the ice , Its still worth reading, I hope second edition will give more focus on breaking the ice with complex examples and give practical examples for data mesh. Since the whole book is practical was expecting something in data vault / data mesh also in deep.Eagerly waiting for second edition
Amazon Verified review Amazon
Anna Jul 19, 2023
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Data modeling has been partially forgotten in the cloud data warehouse scenario and now making a legendary comeback. At the same time, data professionals have been raving about Snowflake Data Cloud.This book offers a clear and practical approach to understanding the combo: data modeling within the Snowflake realm. From fundamental principles to real examples, it's a must-have resource for both beginners and experienced professionals.The author is a good writer. He does a fantastic job explaining hard technical concepts in an easy-to-read & understandable format. We need more educational materials like this.Highly recommended!
Amazon Verified review Amazon
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