Overview

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 Learn Understand dbt and its role in the modern data stack Set up projects using both the cloud-hosted dbt Platform and open source project Connect dbt projects to cloud data warehouses Build scalable models in SQL and Python Configure development, testing, and production environments Capture reusable logic with Jinja macros Incorporate version control with your data transformation code Seamlessly connect your projects using dbt Mesh Build and manage a semantic layer using dbt Deploy dbt using CI/CD best practices 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.

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Author Information

Dustin Dorsey is a data leader and architect who has been building and managing data solutions for more than 16 years. He is currently a leader in the data consulting space and works with companies of all sizes to modernize and scale their data analytics environments. A respected voice in the data community, Dustin is an international speaker and mentor. He has also organized several data community events and user groups in his local community of Nashville, Tennessee. Dustin is a co-author of the popular Apress books Pro Database Migration to Azure and Unlocking dbt. Cameron Cyr is a data fanatic who has spent his career developing data systems that enable valuable use cases such as analytics and machine learning. He specializes in building reliable, scalable architectures with a strong emphasis on data quality. As a data consultant, Cameron provides engineering, architecture, and analytics services. He is also a co-author of Unlocking dbt.

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