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Data Engineering with dbt

You're reading from   Data Engineering with dbt A practical guide to building a cloud-based, pragmatic, and dependable data platform with SQL

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Product type Paperback
Published in Jun 2023
Publisher Packt
ISBN-13 9781803246284
Length 578 pages
Edition 1st Edition
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Author (1):
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Roberto Zagni Roberto Zagni
Author Profile Icon Roberto Zagni
Roberto Zagni
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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 FREE CHAPTER 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

Moving Beyond the Basics

In the previous chapters, we discussed the basic tenets of data engineering, our opinionated approach to the Pragmatic Data Platform (PDP), and we used basic and advanced dbt functionalities to implement it in its basic form.

In this chapter, you will review the best practices to apply modularity in your pipelines to simplify their evolution and maintenance.

Next you will learn how to manage the identity of your entities as it is central to store changes to them and to apply master data management to combine data from different systems.

We will also use macros, the most powerful dbt functionality, to implement the first pattern to store and retrieve the changes in our data according to our discussion of identity management. This allows all developers to use the best practices that senior colleagues have developed.

In this chapter, you will learn about the following topics:

  • Building for modularity
  • Managing identity
  • Master data management...
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