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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

Boosting your confidence and final thoughts

One thing that I hope you have after reading this book is more confidence – the confidence to design and develop a data pipeline and, more importantly, the confidence as a data engineer using Google Cloud Platform.

I will quote the definition of the word confidence from the physiological aspect by the American Psychological Association:

"Confidence is Self-assurance: trust in one's abilities, capacities, and judgment."

By following all the chapters throughout the book, you've learned about the important GCP services related to Data Engineering and tried them out in your environment by completing the hands-on exercises provided. You've tried 19 new technologies from GCP, including BigQuery, Google Cloud Storage, Cloud Composer, DataProc, DataFlow, Pub/Sub, CloudSQL, Google Data Studio, Vertex AI pipeline, Vision AI, Translate AI, AutoML, IAM, Cloud Shell, Cloud Editor, Cloud Build, Google Container...

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