Cameron Cyr – författare

This book shows how dbt is used to build data transformation pipelines that enable dependency management and allow for version control and automated testing. It explains how dbt is revolutionizing data transformation and the advantages that a command-line tool like dbt provides over and above the use of database stored procedures and other ETL and ELT tools that handle data transformations. You’ll see how to create custom-written transformations through simple SQL SELECT statements, eliminating the need for boilerplate code and making it easy to incorporate dbt as the transformation layer in your data warehouse pipelines. Additionally, you will learn how dbt enables data teams to incorporate software engineering best practices such as code reusability, version control, and automated testing into the data transformation process. 

 

Unlocking dbt walks you through using dbt to establish a project, build and modularize SQL models, and execute jobs in away that is easy to maintain and scale as your data ecosystem matures. You’ll begin by establishing and configuring a project, a process covered using both dbt Cloud and dbt Core, so that you can confidently stand up a project using either platform. From there, you’ll move into building transformations with peace of mind that your project will scale appropriately as you continue to develop it. 

 

After learning the basics needed to get started, you’ll continue to build on that foundation by looking at the unique ways in which dbt combines SQL with Jinja to take your code beyond what is capable in normal SQL. You will learn about advanced materializations, building lineage in your data flows, the unlimited potential of macros, and so much more. This book also explores supported file types and the building of Python models. Rounding things out, you will learn features of dbt that will assist you in making your transformation layer production ready. These includehow to implement automated testing, using dbt to generate documentation, and running CI/CD pipelines.

What You Will Learn

Understand what dbt is and how it is used in the modern data stackSet up a project using both dbt Cloud and dbt CoreConnect a dbt project to a cloud data warehouseBuild SQL and Python models that are scalable and maintainableConfigure development, testing, and production environmentsCapture reusable logic in the form of Jinja macrosIncorporate version control with your data transformation code

 

Who This Book Is For

Current and aspiring data professionals, including architects, developers, analysts, engineers, data scientists, and consultants who are beginning the journey of using dbt as part of their data pipeline’s transformation layer. Readers should have a foundational knowledge of writing basic SQL statements, development best practices, and working with data in an analytical context such as a data warehouse.

Master the art of data transformation with the second edition of this trusted guide to dbt.Building on the foundation of the first edition, this updated volume offers a deeper, more comprehensive exploration of dbt’s capabilities—whether you're new to the tool or looking to sharpen your skills. It dives into the latest features and techniques, equipping you with the tools to create scalable, maintainable, and production-ready data transformation pipelines.Unlocking dbt, Second Edition introduces key advancements, including the semantic layer, which allows you to define and manage metrics at scale, and dbt Mesh, empowering organizations to orchestrate decentralized data workflows with confidence. You’ll also explore more advanced testing capabilities, expanded CI/CD and deployment strategies, and enhancements in documentation—such as the newly introduced dbt Catalog.As in the first edition, you’ll learn how to harness dbt’s power to transform raw data into actionable insights, while incorporating software engineering best practices like code reusability, version control, and automated testing. From configuring projects with the dbt Platform or open source dbt to mastering advanced transformations using SQL and Jinja, this book provides everything you need to tackle real-world challenges effectively.What You Will LearnUnderstand dbt and its role in the modern data stackSet up projects using both the cloud-hosted dbt Platform and open source projectConnect dbt projects to cloud data warehousesBuild scalable models in SQL and PythonConfigure development, testing, and production environmentsCapture reusable logic with Jinja macrosIncorporate version control with your data transformation codeSeamlessly connect your projects using dbt MeshBuild and manage a semantic layer using dbtDeploy dbt using CI/CD best practicesWho This Book Is ForCurrent and aspiring data professionals, including architects, developers, analysts, engineers, data scientists, and consultants who are beginning the journey of using dbt as part of their data pipeline’s transformation layer. Readers should have a foundational knowledge of writing basic SQL statements, development best practices, and working with data in an analytical context such as a data warehouse.