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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 FREE CHAPTER
2. Chapter 1: Fundamentals of Data Engineering 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 conclude 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, 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 present concepts. 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...

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