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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

We've learned a lot of new things in this chapter about the cloud and GCP – let's summarize it. We started this chapter by accessing the GCP console for the first time. We then narrowed things down to find our first priority GCP services for data engineers to focus on.

And we closed the chapter by familiarizing ourselves with important features and terminologies such as quotas and service accounts. 

In the next chapter, we will do a lot more step-by-step, hands-on exercises with practical use cases using the services that we introduced in this chapter to build data solutions. So, make sure you've set up the GCP console properly and are ready for the exercises. In the next chapter, we will start by practicing developing a data warehouse. As we've learned in this chapter, the cloud data warehouse in GCP is BigQuery. We will start by learning about this very famous service – and one of the most important – for GCP data engineers...

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