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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Summary

As we draw this chapter to a close, let’s revisit the pivotal role that an Agile SDLC plays in data engineering. Agile methodologies, renowned for their adaptability and iterative nature, are indispensable for effectively managing the complexities of modern data systems. Tailoring these practices to fit the nuances of data engineering operations brings forth the level of flexibility and responsiveness needed in today’s fast-evolving tech world.

In this context, the role of leadership and the cultivation of an Agile culture within organizations cannot be overstated. Leaders play a pivotal role in advocating for and embedding Agile principles, ensuring that these methodologies are not merely adopted but are ingrained within the team’s ethos and practices.

Reflecting on the core concepts discussed, it becomes clear that a customized approach to Agile methodologies and SDLC processes is crucial. These tailored practices, woven into the fabric of data...