Book Image

Data Engineering with Google Cloud Platform

By : Adi Wijaya
3 (1)
Book Image

Data Engineering with Google Cloud Platform

3 (1)
By: Adi Wijaya

Overview of this book

With this book, you'll understand how the highly scalable Google Cloud Platform (GCP) enables data engineers to create end-to-end data pipelines right from storing and processing data and workflow orchestration to presenting data through visualization dashboards. Starting with a quick overview of the fundamental concepts of data engineering, you'll learn the various responsibilities of a data engineer and how GCP plays a vital role in fulfilling those responsibilities. As you progress through the chapters, you'll be able to leverage GCP products to build a sample data warehouse using Cloud Storage and BigQuery and a data lake using Dataproc. The book gradually takes you through operations such as data ingestion, data cleansing, transformation, and integrating data with other sources. You'll learn how to design IAM for data governance, deploy ML pipelines with the Vertex AI, leverage pre-built GCP models as a service, and visualize data with Google Data Studio to build compelling reports. Finally, you'll find tips on how to boost your career as a data engineer, take the Professional Data Engineer certification exam, and get ready to become an expert in data engineering with GCP. By the end of this data engineering book, you'll have developed the skills to perform core data engineering tasks and build efficient ETL data pipelines with GCP.
Table of Contents (17 chapters)
Section 1: Getting Started with Data Engineering with GCP
Section 2: Building Solutions with GCP Components
Section 3: Key Strategies for Architecting Top-Notch Data Pipelines


There is too much information; too many plans; it's complicated. We live in a world where there is more and more information that is 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 a great number of technology options: cloud versus non-cloud; big data database versus traditional; self-managed versus a managed service; and many more.

When they decide to use the cloud on GCP, 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 of this book is to help you narrow down the information. This book will help you narrow down 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, and will give you a clear focus. By reading the book and following the exercises, you will learn the most relevant and clear path to start and boost your career in data engineering using GCP.