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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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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

Understanding what the cloud is

Renting someone else's server: this definition of the cloud is my favorite, very simple, to the point, definition of what the cloud really is. So as long as you don't need to buy your own machine to store and process data, you are using the cloud. 

But increasingly, after some leading cloud providers such as Google Cloud having gained more traction and technology maturity, the terminology is becoming representative of sets of architecture, managed services, and highly scalable environments that define how we build solutions. For data engineering, that means building data products using collections of services, APIs, and trusting the underlying infrastructure of the cloud provider one hundred percent.

The difference between the cloud and non-cloud era

If we want to compare the cloud with the non-cloud era from a data engineering perspective, we will find that almost all the data engineering principles are the same. But from a technology...

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