Wow! eBook
Data Engineering with dbt: A practical guide to building a cloud-based, pragmatic, and dependable data platform with SQL
Author(s): Roberto Zagni (Author)
- Publisher: Packt Publishing
- Publication Date: 30 Jun. 2023
- Language: English
- Print length: 578 pages
- ISBN-10: 1803246286
- ISBN-13: 9781803246284
Book Description
Use easy-to-apply patterns in SQL and Python to adopt modern analytics engineering to build agile platforms with dbt that are well-tested and simple to extend and run
Purchase of the print or Kindle book includes a free PDF eBook
Key Features
- Build a solid dbt base and learn data modeling and the modern data stack to become an analytics engineer
- Build automated and reliable pipelines to deploy, test, run, and monitor ELTs with dbt Cloud
- Guided dbt + Snowflake project to build a pattern-based architecture that delivers reliable datasets
Book Description
dbt Cloud helps professional analytics engineers automate the application of powerful and proven patterns to transform data from ingestion to delivery, enabling real DataOps.
This book begins by introducing you to dbt and its role in the data stack, along with how it uses simple SQL to build your data platform, helping you and your team work better together. You’ll find out how to leverage data modeling, data quality, master data management, and more to build a simple-to-understand and future-proof solution. As you advance, you’ll explore the modern data stack, understand how data-related careers are changing, and see how dbt enables this transition into the emerging role of an analytics engineer. The chapters help you build a sample project using the free version of dbt Cloud, Snowflake, and GitHub to create a professional DevOps setup with continuous integration, automated deployment, ELT run, scheduling, and monitoring, solving practical cases you encounter in your daily work.
By the end of this dbt book, you’ll be able to build an end-to-end pragmatic data platform by ingesting data exported from your source systems, coding the needed transformations, including master data and the desired business rules, and building well-formed dimensional models or wide tables that’ll enable you to build reports with the BI tool of your choice.
What you will learn
- Create a dbt Cloud account and understand the ELT workflow
- Combine Snowflake and dbt for building modern data engineering pipelines
- Use SQL to transform raw data into usable data, and test its accuracy
- Write dbt macros and use Jinja to apply software engineering principles
- Test data and transformations to ensure reliability and data quality
- Build a lightweight pragmatic data platform using proven patterns
- Write easy-to-maintain idempotent code using dbt materialization
Who this book is for
This book is for data engineers, analytics engineers, BI professionals, and data analysts who want to learn how to build simple, futureproof, and maintainable data platforms in an agile way. Project managers, data team managers, and decision makers looking to understand the importance of building a data platform and foster a culture of high-performing data teams will also find this book useful. Basic knowledge of SQL and data modeling will help you get the most out of the many layers of this book. The book also includes primers on many data-related subjects to help juniors get started.
Table of Contents
- Basics of SQL to transform data
- Setting up your dbt Cloud development environment
- Data modelling for data engineering
- Analytics Engineering as the New Core of Data Engineering
- Transforming data with dbt
- Writing Maintainable Code
- Working with Dimensional Data
- Delivering Consistency In Your Code
- Delivering Reliability In Your Data
- Agile development
- Collaboration
- Deployment, Execution and Documentation Automation
- Moving beyond basics
- Enhancing Software Quality
- Patterns for frequent use cases
Editorial Reviews
Review
“Roberto Zagni has done an outstanding job in his new book Data Engineering with dbt. Whether you are new to data engineering or a seasoned pro, this book will become your go-to resource as you build out your cloud-based data platforms and data pipelines using dbt. Roberto gives exceptionally detailed definitions, guidelines, best practices (like test your code!), examples, and tutorials throughout the book. If you learn by example, you will love this easy-to-follow book. A big plus, to me, is that he also introduces you to Snowflake (and how to create your free account) as well as dedicating an entire chapter to data modeling (including Data Vault) and its importance. Well done!”
—
Kent Graziano, The Data Warrior, Strategic Advisor, Data Vault Master, Author
“This book is a great guide to software engineering applied to data projects. Through the GIT chapters, you will get familiar with the infrastructure, as well as the collaboration with your team, and the versioning. The chapters about DBT will teach you about the toolset, explaining the automation of transformations, automation of tests, lineage, impact analysis, and more.
At the core of the book is the idea of creating a pragmatic data platform that tries to be as much as possible stateless, so that you can easily apply any change.
The book also provides a good introduction to data modeling, explaining different styles (including Inmon, Kimball, Data Vault, and Unified Star Schema) and master data management with practical examples.
This is a must-have for every organization that wants to be prepared for the scalability of processes and teams.”
—
Francesco Puppini, Author, speaker, and Data Modeling innovator
About the Author
Roberto Zagni is a senior leader with extensive hands-on experience in data architecture, software development and agile methodologies. Roberto is an Electronic Engineer by training with a special interest in bringing software engineering best practices to cloud data platforms and growing great teams that enjoy what they do. He has been helping companies to better use their data, and now to transition to cloud based Data Automation with an agile mindset and proper SW engineering tools and processes, aka DataOps. Roberto also coaches data teams hands-on about practical data architecture and the use of patterns, testing, version control and agile collaboration. Since 2019 his go to tools are dbt, dbt Cloud and Snowflake or BigQuery.
