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

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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

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People, technology, and processes

When reflecting on the goal of the book, which is to provide you with data engineering best practices, we focused on people, technology, and processes first, understanding the answers to the question why? For example, Why did you design it like that? Why did you not consider these options? Why did you go in that direction, rather than that direction? All these choices are driven by your enterprise and IT mission and vision. Otherwise, you will have no ground to stand on when challenged and, as an engineer, expect to be challenged frequently. Together, the mission and vision enable you to craft an architecture that organizes your thinking and provides guardrails for your design choices.

Working with other people

Transparency is required to meet the challenges of the skeptics you will encounter. “Build it and they will come” is just not going to happen without a healthy dose of social engineering before you attempt to engineer a solution...