Google Cloud Certified Professional Data Engineer Certification Guide
Get certified and develop expert-level data engineering skills with Google Cloud Platform
Will be published approx. on 29. May 2026
Book
Paperback/Softback
978-1-83664-131-5 (ISBN)
Description
A guide to pass the GCP Professional Data Engineer exam on your first attempt and upgrade your data engineering skills on GCP.
Key Features
Fully understand the certification exam content and exam objectives
Consolidate your knowledge of all essential exam topics and key concepts
Get realistic experience of answering exam-style questions
Develop practical skills for everyday use
Purchase of this book unlocks access to web-based exam prep resources including mock exams, flashcards, exam tips
Book DescriptionThe GCP Professional Data Engineer certification validates the fundamental knowledge required to perform data engineering tasks and use GCP services to enhance data engineering processes and further your career in the data engineering/architecting field. This book is a best-in-class study guide that fully covers the GCP Professional Data Engineer exam objectives and helps you pass the exam first time.
Complete with clear explanations, chapter review questions, realistic mock exams, and pragmatic solutions, this guide will help you master the core exam concepts and build the understanding you need to go into the exam with the skills and confidence to get the best result you can.
With the help of relevant examples, you'll learn fundamental data engineering concepts such as data warehousing and data security. As you progress, you'll delve into the important domains of the exam, including data pipelining, data migration, and data processing.
Unlike other study guides, this book contains logical reasoning behind the choice of correct answers based in scenarios and provide you with excellent tips regarding the optimal use of each service, and gives you everything you need to pass the exam and enhance your prospects in the data engineering field.What you will learn
Create data solutions and pipelines in GCP
Analyze and transform data into useful information
Apply data engineering concepts to real scenarios
Create secure, cost-effective, valuable GCP workloads
Work in the GCP environment with industry best practices
Who this book is forThis book is for data engineers who want a reliable source for the key concepts and terms present in the most prestigious and highly-sought-after cloud-based data engineering certification. This book will help you improve your data engineering in GCP skills to give you a better chance at earning the GCP Professional Data Engineer Certification.
You will already be familiar with the Google Cloud Platform, having either explored it (professionally or personally) for at least a year. You should also have some familiarity with basic data concepts (such as types of data and basic SQL knowledge).
Key Features
Fully understand the certification exam content and exam objectives
Consolidate your knowledge of all essential exam topics and key concepts
Get realistic experience of answering exam-style questions
Develop practical skills for everyday use
Purchase of this book unlocks access to web-based exam prep resources including mock exams, flashcards, exam tips
Book DescriptionThe GCP Professional Data Engineer certification validates the fundamental knowledge required to perform data engineering tasks and use GCP services to enhance data engineering processes and further your career in the data engineering/architecting field. This book is a best-in-class study guide that fully covers the GCP Professional Data Engineer exam objectives and helps you pass the exam first time.
Complete with clear explanations, chapter review questions, realistic mock exams, and pragmatic solutions, this guide will help you master the core exam concepts and build the understanding you need to go into the exam with the skills and confidence to get the best result you can.
With the help of relevant examples, you'll learn fundamental data engineering concepts such as data warehousing and data security. As you progress, you'll delve into the important domains of the exam, including data pipelining, data migration, and data processing.
Unlike other study guides, this book contains logical reasoning behind the choice of correct answers based in scenarios and provide you with excellent tips regarding the optimal use of each service, and gives you everything you need to pass the exam and enhance your prospects in the data engineering field.What you will learn
Create data solutions and pipelines in GCP
Analyze and transform data into useful information
Apply data engineering concepts to real scenarios
Create secure, cost-effective, valuable GCP workloads
Work in the GCP environment with industry best practices
Who this book is forThis book is for data engineers who want a reliable source for the key concepts and terms present in the most prestigious and highly-sought-after cloud-based data engineering certification. This book will help you improve your data engineering in GCP skills to give you a better chance at earning the GCP Professional Data Engineer Certification.
You will already be familiar with the Google Cloud Platform, having either explored it (professionally or personally) for at least a year. You should also have some familiarity with basic data concepts (such as types of data and basic SQL knowledge).
More details
Language
English
Place of publication
Birmingham
United Kingdom
Dimensions
Height: 235 mm
Width: 191 mm
ISBN-13
978-1-83664-131-5 (9781836641315)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Persons
Ankur Roy is a Solutions Architect who works for Online Partner AB in Stockholm, Sweden. In his role, he works with some of the largest companies, education providers and municipalities in Sweden with projects regarding cloud infrastructure and data usage, largely in Google Cloud Platform and Google Workspace. He currently holds all available GCP-based certifications. He has previously written a book titled Hands-On Python with DevOps. Outside of work, Ankur enjoys creative ventures in writing, in music making and podcasting. Sireesha Pulipati is a seasoned data and analytics professional with extensive experience across healthcare, media, retail, and technology. At Attain, she leads development of scalable data products that drive commerce insights for Fortune 500 brands.
Previously, she led analytics and data solutions at Google for Search and Google Cloud. A Google Developer Expert for Cloud, she holds GCP certifications including Professional Data Engineer and Cloud Architect.
She has an MBA, a bachelor's in Electrical Engineering, and recently completed a Business Leadership program at Stanford. Outside work, Sireesha mentors aspiring professionals, volunteers in language education, and enjoys hiking and reading books.
Previously, she led analytics and data solutions at Google for Search and Google Cloud. A Google Developer Expert for Cloud, she holds GCP certifications including Professional Data Engineer and Cloud Architect.
She has an MBA, a bachelor's in Electrical Engineering, and recently completed a Business Leadership program at Stanford. Outside work, Sireesha mentors aspiring professionals, volunteers in language education, and enjoys hiking and reading books.
Content
Table of Contents
Storing Data - Service Selection
Storing Data - Data Warehousing
Storing Data - Data Lakes
Storing Data - Data Mesh
Data Preparation and Analysis - Data Visualization
Data Preparation and Analysis - Data Sharing
Data Preparation and Analysis - Data Exploration and Analysis
Data Processing Design - Security and Compliance
Data Processing Design - Reliability and Fidelity
Data Processing Design - Flexibility and Portability
Data Processing Design - Data Migrations
Data Engineering and Processing - Planning Pipelines
Data Engineering and Processing - Building Pipelines
Data Engineering and Processing - Pipeline Operations
Maintenance and Automation - Resource Usage and Cost Optimization
Maintenance and Automation - Automating and Backing Up Processes
Storing Data - Service Selection
Storing Data - Data Warehousing
Storing Data - Data Lakes
Storing Data - Data Mesh
Data Preparation and Analysis - Data Visualization
Data Preparation and Analysis - Data Sharing
Data Preparation and Analysis - Data Exploration and Analysis
Data Processing Design - Security and Compliance
Data Processing Design - Reliability and Fidelity
Data Processing Design - Flexibility and Portability
Data Processing Design - Data Migrations
Data Engineering and Processing - Planning Pipelines
Data Engineering and Processing - Building Pipelines
Data Engineering and Processing - Pipeline Operations
Maintenance and Automation - Resource Usage and Cost Optimization
Maintenance and Automation - Automating and Backing Up Processes