Название: Unlocking dbt: Design and Deploy Transformations in Your Cloud Data Warehouse, 2nd Edition
Автор: Dustin Dorsey, Cameron Cyr
Издательство: Apress
Год: 2025
Страниц: 479
Язык: английский
Формат: pdf
Размер: 14.7 MB

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 Is dbt? At its simplest definition, dbt (or data build tool, as it was previously called) is an open source data transformation tool commonly used for modeling data in data warehouses. It enables data professionals who are comfortable writing SQL to transform data in their warehouses more effectively. At a more granular level, it is a tool that has a development framework that combines modular SQL with software engineering best practices to create a better, faster, and more reliable data transformation experience. Modular SQL refers to the practice of breaking down SQL code into smaller, reusable chunks so that it can be more easily maintained, tested, and reused. Other best practices that dbt lends itself well to include version control, documentation, DevOps, and so on.

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.