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Data Engineering with Google Cloud Platform

You're reading from   Data Engineering with Google Cloud Platform A practical guide to operationalizing scalable data analytics systems on GCP

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Product type Paperback
Published in Mar 2022
Publisher Packt
ISBN-13 9781800561328
Length 440 pages
Edition 1st 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 (17) Chapters Close

Preface 1. Section 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. Section 2: Building Solutions with GCP Components
5. Chapter 3: Building a Data Warehouse in BigQuery 6. Chapter 4: Building Orchestration 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 for Making Data-Driven Decisions with Data Studio 10. Chapter 8: Building Machine Learning Solutions on Google Cloud Platform 11. Section 3: Key Strategies for Architecting Top-Notch Data Pipelines
12. Chapter 9: User and Project Management in GCP 13. Chapter 10: Cost Strategy in GCP 14. Chapter 11: CI/CD on Google Cloud Platform for Data Engineers 15. Chapter 12: Boosting Your Confidence as a Data Engineer 16. 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. But lately, it's more and more common for data engineers to follow this practice in big organizations.

We started this chapter by talking about the high-level concepts and ended it with an exercise that showed how data engineers can use CI/CD in a data project. In the exercises, we used Cloud Build, Cloud Source Repository, and Google Container Registry. 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 all the...

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