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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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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

Testing the right things in the right places

In the previous sections, we saw how easy is to add tests in dbt; most of the time, you just add a tests: property with a few test names under a table or column in a YAML file.

Adding tests is so simple that it is easy to go overboard and start testing everything and everywhere, but please refrain from doing that, and remember that tests are code and, therefore, bring with them their fair share of errors (wrong application or configuration of generic tests from libraries and coding errors in our own singular tests), maintenance (false positives, errors without business value that can just be ignored, and constant test refactoring), and consequences (ignoring important tests because of constant test failure fatigue).

Tests also take time and money to execute, so waiting for useless tests to complete is a total waste of money, and of a developer’s time when they run tests in their development environments. It’s also not...

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