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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

IT operational best practices overview

Just looking at the technology stack reported by SD Times in 2017, from Atlassian {https://packt-debp.link/sV36qr} in Figure 11.1 {https://packt-debp.link/TdzvqG}, you can see that the number of products associated with the DevOps cycle is daunting:

Figure 11.1 – Atlassian Stack

Figure 11.1 – Atlassian Stack

What you will need is a documented operational manifesto driven by best practices that will help make tool selection and process definition for your ecosystem possible. For this manifesto, you will not want to begin from a green field. So, let’s begin with the Information Technology Infrastructure Library (ITIL).

From other chapters, you will recall that we mentioned the need for ITIL when building out your Information Technology Service Management (ITSM) process framework. The following quote from Gene Kim will underline this need:

“The DevOps Movement fits perfectly with ITSM , ITIL and ITSM still are the best...

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