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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

Technical requirements

In this chapter’s exercises, we will use the following GCP services:

  • IAM
  • BigQuery
  • Google Cloud Storage (GCS)

If you’ve never opened any of these services in your GCP console, open them and enable the application programming interface (API). We will also use an open source software called Terraform to help us provision the GCP services using code. It can be downloaded from their public website at https://www.terraform.io/downloads.html. The step-by-step installation will be discussed in the Exercise – creating and running basic Terraform scripts section.

Make sure you have your GCP console, Cloud Shell, and Cloud Shell Editor ready.

Download the example code and the dataset from https://github.com/PacktPublishing/Data-Engineering-with-Google-Cloud-Platform-Second-Edition/tree/main/chapter-9/code.

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