You're reading from Data Engineering Best Practices Architect robust and cost-effective data solutions in the cloud era

Product type Paperback

Published in Oct 2024

Publisher Packt

ISBN-13 9781803244983

Length 550 pages

Edition 1st Edition

Languages

SQL

Tools

Google cloud SQL

Concepts

Data Engineering

Authors (2):

David Larochelle

Richard J. Schiller

View More author details

Table of Contents (21) Chapters

Preface

1. Chapter 1: Overview of the Business Problem Statement FREE CHAPTER

2. Chapter 2: A Data Engineer’s Journey – Background Challenges

3. Chapter 3: A Data Engineer’s Journey – IT’s Vision and Mission

4. Chapter 4: Architecture Principles

5. Chapter 5: Architecture Framework – Conceptual Architecture Best Practices

6. Chapter 6: Architecture Framework – Logical Architecture Best Practices

7. Chapter 7: Architecture Framework – Physical Architecture Best Practices

8. Chapter 8: Software Engineering Best Practice Considerations

9. Chapter 9: Key Considerations for Agile SDLC Best Practices

10. Chapter 10: Key Considerations for Quality Testing Best Practices

11. Chapter 11: Key Considerations for IT Operational Service Best Practices

12. Chapter 12: Key Considerations for Data Service Best Practices

13. Chapter 13: Key Considerations for Management Best Practices

14. Chapter 14: Key Considerations for Data Delivery Best Practices

15. Chapter 15: Other Considerations – Measures, Calculations, Restatements, and Data Science Best Practices

16. Chapter 16: Machine Learning Pipeline Best Practices and Processes

17. Chapter 17: Takeaway Summary – Putting It All Together

18. Chapter 18: Appendix and Use Cases

19. Index

Why subscribe?

20. Other Books You May Enjoy

Test framework example

Now that you have become aware of some of the approaches to testing, it’s time to look at a practical example and for that, we have to begin with key drivers. Please look at Figure 10.1, where you can see a test framework that you can take into account as you develop your solution. It should be formalized and made available to all those on the solution’s various project teams to utilize. In Figure 10.1 you can see that your test framework, integration, and best practices work together to form the scope of your test effort:

Figure 10.1 – Azure DevOps scope

Remember that the goal is to reduce the overhead of testing and make it as easy as possible to run tests. The developers and testers need to be able to catch deviations from the status quo as development sprints release code into various developed environments. You will know that the system is minimally up and running based on integration tests that are running...