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Data Engineering Best Practices

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

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Product type Paperback
Published in Oct 2024
Publisher Packt
ISBN-13 9781803244983
Length 550 pages
Edition 1st Edition
Languages
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Authors (2):
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David Larochelle David Larochelle
Author Profile Icon David Larochelle
David Larochelle
Richard J. Schiller Richard J. Schiller
Author Profile Icon Richard J. Schiller
Richard J. Schiller
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Toc

Table of Contents (21) Chapters Close

Preface 1. Chapter 1: Overview of the Business Problem Statement 2. Chapter 2: A Data Engineer’s Journey – Background Challenges FREE CHAPTER 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 20. Other Books You May Enjoy

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...

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