Data Engineering with dbt Год издания: 2023 Автор: Zagni R. Издательство: Packt ISBN: 9781803246284 Язык: Английский Формат: EPUB Качество: Издательский макет или текст (eBook) Интерактивное оглавление: Да Количество страниц: 578 Описание: 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.
Оглавление
Preface Part 1: The Foundations of Data Engineering Chapter 1: The Basics of SQL to Transform Data Chapter 2: Setting Up Your dbt Cloud Development Environment Chapter 3: Data Modeling for Data Engineering Chapter 4: Analytics Engineering as the New Core of Data Engineering Chapter 5: Transforming Data with dbt Part 2: Agile Data Engineering with dbt Chapter 6: Writing Maintainable Code Chapter 7: Working with Dimensional Data Chapter 8: Delivering Consistency in Your Data Chapter 9: Delivering Reliability in Your Data Chapter 10: Agile Development Chapter 11: Team Collaboration Part 3: Hands-On Best Practices for Simple, Future-Proof Data Platforms Chapter 12: Deployment, Execution, and Documentation Automation Chapter 13: Moving Beyond the Basics Chapter 14: Enhancing Software Quality Chapter 15: Patterns for Frequent Use Cases Index Other Books You May Enjoy
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