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Data Engineering with Google Cloud Platform

You're reading from   Data Engineering with Google Cloud Platform A guide to leveling up as a data engineer by building a scalable data platform with Google Cloud

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Product type Paperback
Published in Apr 2024
Publisher Packt
ISBN-13 9781835080115
Length 476 pages
Edition 2nd Edition
Languages
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Author (1):
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Adi Wijaya Adi Wijaya
Author Profile Icon Adi Wijaya
Adi Wijaya
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Toc

Table of Contents (19) Chapters Close

Preface 1. Part 1: Getting Started with Data Engineering with GCP
2. Chapter 1: Fundamentals of Data Engineering FREE CHAPTER 3. Chapter 2: Big Data Capabilities on GCP 4. Part 2: Build Solutions with GCP Components
5. Chapter 3: Building a Data Warehouse in BigQuery 6. Chapter 4: Building Workflows for Batch Data Loading Using Cloud Composer 7. Chapter 5: Building a Data Lake Using Dataproc 8. Chapter 6: Processing Streaming Data with Pub/Sub and Dataflow 9. Chapter 7: Visualizing Data to Make Data-Driven Decisions with Looker Studio 10. Chapter 8: Building Machine Learning Solutions on GCP 11. Part 3: Key Strategies for Architecting Top-Notch Solutions
12. Chapter 9: User and Project Management in GCP 13. Chapter 10: Data Governance in GCP 14. Chapter 11: Cost Strategy in GCP 15. Chapter 12: CI/CD on GCP for Data Engineers 16. Chapter 13: Boosting Your Confidence as a Data Engineer 17. Index 18. Other Books You May Enjoy

Summary

In this chapter, we learned about how CI/CD works in GCP services. More specifically, we learned about this from the perspective of a data engineer. CI/CD is a big topic by itself and is more mature in the software development practice. However, lately, it’s become more and more common for data engineers to follow this practice in big organizations.

We started this chapter by talking about high-level concepts and ended it with an exercise that showed how data engineers can use CI/CD in a data project. We used Cloud Build, a Cloud Source Repository, and Google Container Registry in the exercises. Understanding these concepts and what kind of technologies are involved were the two main goals of this chapter. If you want to learn more about DevOps practices, containers, and unit testing, check out the links in the Further reading section.

This was the final technical chapter in this book. If you have read all the chapters in this book, then you’ve learned about...

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