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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

Product type Paperback

Published in Mar 2022

Publisher Packt

ISBN-13 9781800561328

Length 440 pages

Edition 1st Edition

Languages

Python

Tools

Google Cloud Platform

Concepts

Data Analysis

Author (1):

Adi Wijaya

View More author details

Table of Contents (17) Chapters

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

Technical requirements

Before we begin the chapter, make sure you have the following prerequisites ready.

In this chapter's exercises, we will use these GCP services: Dataproc, GCS, BigQuery, and Cloud Composer. If you never open any of these services in your GCP console, open it and enable the API.

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

Download the example code and the dataset here: https://github.com/PacktPublishing/Data-Engineering-with-Google-Cloud-Platform/tree/main/chapter-5.

Be aware of the cost that might occur from Dataproc and the Cloud Composer cluster. Make sure you delete all the environments after the exercises to prevent any unexpected costs.

The rest of the chapter is locked

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Authors (1)

Adi Wijaya

Adi Wijaya

Adi Wijaya thrives in the dynamic environment of Indonesia, where he enjoys music, art, sports, technology, and analytics. His inquisitive mind is fueled by a passion for data and human nature which he sees as valuable lenses to understand the world. This curiosity naturally led him to the field of data science, where he co-founded DataLabs Indonesia and now leverages his expertise as a Data Strategic Cloud Engineer at Google. Adi is driven by a dual mission: empowering organizations to build robust analytics ecosystems and fostering the growth of talented data practitioners. He's deeply committed to the potential of Big Data and Analytics, believing it can revolutionize not just businesses, but also improve government efficiency, and environmental sustainability, and ultimately, enhance human lives.

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