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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 concluded everything we've learned throughout this book. We started the chapter by overviewing the certification options from Google Cloud. There, we covered most of the GCP services that are part of the certification. But for those that weren't covered, I suggest that you take a look at those services by looking at other resources.

In the next section, we looked at some quiz questions to help you gain a better understanding of the types of questions that will be asked and the format of the certification. I highly suggest that you review the other chapters if you missed some points from any of these questions.

Finally, I shared my thoughts on the past, present, and future of Data Engineering. Do remember that big data and the cloud are the present. You, as a data engineer, are and will be the center of it. Today is the best era for Data Engineering and I'm 100% confident in this. I hope that you enjoyed reading this book and have a...

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