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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
Author (1):
Roberto Zagni Roberto Zagni
Profile icon Roberto Zagni
Toc

Table of Contents (21) Chapters close

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 20. Other Books You May Enjoy

Building on the shoulders of giants – dbt packages

We have been writing our models and macros using only the base dbt functionality. In this section, we will see some existing libraries, called packages in dbt, and how we can import them to increase our productivity.

Using only dbt or Java or Python standard functionalities, you can build everything that you need. Doing everything by yourself does not pose an absolute limitation, but in all languages, the availability of libraries, collections of well-tested code to do frequent or complex tasks that you can easily download and use to accomplish complex tasks, has greatly augmented the productivity of programmers and their ability to solve more complex problems.

Using libraries, you can concentrate on the core of your problem and rely on a lot of other smart people’s knowledge and experience to reduce the complexity of your project, saving a lot of time.

You can reuse the code written by experts in areas that...

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