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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
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

Preface

There is too much information – too many options and plans. Things are complicated. We live in a world where there is more and more information, which can be as problematic as too little information, and I’m aware that this condition applies when people want to start doing data engineering in the cloud, specifically Google Cloud Platform (GCP) in this book.

When people want to embark on a career in data, there are so many different roles whose definitions sometimes vary from one company to the next.

When someone chooses to be a data engineer, there are many technology options – cloud versus non-cloud, a big data database versus a transactional database, a self-managed service versus a managed service, and so on.

Upon deciding to use the cloud on GCP, you will find that the public documentation contains a wide variety of product options and tutorials.

In this book, instead of adding further dimensions to the data engineering and GCP products, the main goal is to help you narrow down the information. This book will help you focus on all the important concepts and components from the vast array of information available on the internet.

The guidance and exercises are based on the writer’s experience in the field. By reading the book and following exercises, you will learn the most relevant and clear path to start and boost your career in data engineering using GCP.

Readers of the first edition have consistently reported using the book to successfully achieve GCP certification and launch careers as GCP data engineers. Building on this proven approach, in this second edition, we’ve updated all information to reflect the latest GCP landscape, while preserving the book’s successful format.

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