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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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Table of Contents (19) Chapters Close

Preface 1. Part 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. 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

Understanding the GCP organization, folder, and project hierarchy

A GCP project organizes all your Google Cloud resources. Resources in GCP can be services, billing, accounts, authentications, logs, and monitoring. Resources from one project can be used and accessed by other resources from other projects. So long as the permissions to resources are set correctly, there is no restriction on accessing them between projects.

For example, look at Figure 9.3. The cloud SQL database from the core-apps-and-db project can be accessed by Cloud Composer in dwh-project. Let’s look at another example – a user account that was created in the core-apps-and-db project can access data from BigQuery in the data project. Note that accounts and authentications are also resources. The key point here is that resources in GCP projects are not isolated.

Now, let’s talk about the GCP folder. One GCP folder can contain one to many GCP projects. GCP folders can also contain one to...

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