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Data Engineering with dbt

You're reading from Data Engineering with dbt

Product type Book

Published in Jun 2023

Publisher Packt

ISBN-13 9781803246284

Pages 578 pages

Edition 1st Edition

Languages

Concepts

Author (1):

Roberto Zagni

Table of Contents (21) Chapters

Preface

1. Part 1: The Foundations of Data Engineering

2. Chapter 1: The Basics of SQL to Transform Data

3. Chapter 2: Setting Up Your dbt Cloud Development Environment

4. Chapter 3: Data Modeling for Data Engineering

5. Chapter 4: Analytics Engineering as the New Core of Data Engineering

6. Chapter 5: Transforming Data with dbt

7. Part 2: Agile Data Engineering with dbt

8. Chapter 6: Writing Maintainable Code

9. Chapter 7: Working with Dimensional Data

10. Chapter 8: Delivering Consistency in Your Data

11. Chapter 9: Delivering Reliability in Your Data

12. Chapter 10: Agile Development

13. Chapter 11: Team Collaboration

14. Part 3: Hands-On Best Practices for Simple, Future-Proof Data Platforms

15. Chapter 12: Deployment, Execution, and Documentation Automation

16. Chapter 13: Moving Beyond the Basics

17. Chapter 14: Enhancing Software Quality

18. Chapter 15: Patterns for Frequent Use Cases

19. Index

Why subscribe?

20. Other Books You May Enjoy

Summary

In this chapter, you have learned about the full data life cycle, and you became familiar with DataOps and the modern data platform concepts that make it possible to develop data projects with similar way of working and to achieve the same satisfaction level as software projects developed using a DevOps approach.

Well done!

We introduced the figure of the analytics engineer, who takes the central role of building the core of a modern data platform, and we saw the best practices and principles that we can adopt from software engineering to make our work on data projects more reliable and satisfying for us and other stakeholders.

With this chapter, we close the first part of this book, which has introduced you to the key elements of data engineering and will enable you to better understand how we work with dbt.

In the next chapter, Agile Data Engineering with dbt, you will start to learn about the core functionalities of dbt and you will start building the first models...

The rest of the chapter is locked

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Authors (1)

Roberto Zagni

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.

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