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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Detailed capabilities of the ingestion zones

The ingestion zones are comprised of various instances of conceptual raw zones defined in the conceptual architecture. Capabilities will be mapped to features in this chapter of the book. ETL pipelines and bronze data standards will be discussed because the total output of the ingestion zone will be the bronze data used in the downstream transformation zones.

ETL data pipelines

There are features of the logical architecture that need to be assessed for your solution. Integrations are very important to dataflows in a pipeline factory. Any vendor tool-driven approach with the features needed to facilitate a robust integration blueprint can speed up development and shorten development delivery timelines. You may then ask the following:

What are some data integration best practices?
So, what do we recommend for the electronic data interchange (EDI) features needed for your solution?

Let’s get answers to these...