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)
1
Section 1: Getting Started with Data Engineering with GCP
4
Section 2: Building Solutions with GCP Components
11
Section 3: Key Strategies for Architecting Top-Notch Data Pipelines

To get the most out of this book

To successfully follow the examples in this book, you need a GCP account and project. If, at this point, you don't have a GCP account and project, don't worry. We will cover that as part of the exercises in this book.

Occasionally, we will use the free tier from GCP for practice, but be aware that some products might not have free tiers. Notes will be provided if this is the case.

All the exercises in this book can be completed without any additional software installation. The exercises will be done in the GCP console that you can open from any operating system using your favorite browser.

You should be familiar with basic programming languages. In this book, I will focus on utilizing Python and the Linux command line.

If you are using the digital version of this book, we advise you to type the code yourself or access the code from the book's GitHub repository (a link is available in the next section). Doing so will help you avoid any potential errors related to the copying and pasting of code.

This book is not positioned to replace GCP public documentation. Hence, comprehensive information on every single feature of GCP services might not be available in this book. We also won't use all the GCP services that are available. For such information, you can always check the public documentation.

Remember that the main goal of this book is to help you narrow down information. Use this book as your step-by-step guide to build solutions to common challenges facing data engineers. Follow the patterns from the exercises, the relationship between concepts, important GCP services, and best practices. Always use the hands-on exercises so you can experience working with GCP.