Wow! eBook
Data Engineering with Google Cloud Platform: A guide to leveling up as a data engineer by building a scalable data platform with Google Cloud 2nd Edition
Author(s): Adi Wijaya (Author)
- Publisher: Packt Publishing
- Publication Date: 30 April 2024
- Edition: 2nd
- Language: English
- Print length: 476 pages
- ISBN-10: 1835080111
- ISBN-13: 9781835080115
Book Description
Become a successful data engineer by building and deploying your own data pipelines on Google Cloud, including making key architectural decisions
Key Features
- Get up to speed with data governance on Google Cloud
- Learn how to use various Google Cloud products like Dataform, DLP, Dataplex, Dataproc Serverless, and Datastream
- Boost your confidence by getting Google Cloud data engineering certification guidance from real exam experiences
- Purchase of the print or Kindle book includes a free PDF eBook
Book Description
The second edition of Data Engineering with Google Cloud builds upon the success of the first edition by offering enhanced clarity and depth to data professionals navigating the intricate landscape of data engineering.
Beyond its foundational lessons, this new edition delves into the essential realm of data governance within Google Cloud, providing you with invaluable insights into managing and optimizing data resources effectively. Written by a Data Strategic Cloud Engineer at Google, this book helps you stay ahead of the curve by guiding you through the latest technological advancements in the Google Cloud ecosystem. You’ll cover essential aspects, from exploring Cloud Composer 2 to the evolution of Airflow 2.5. Additionally, you’ll explore how to work with cutting-edge tools like Dataform, DLP, Dataplex, Dataproc Serverless, and Datastream to perform data governance on datasets.
By the end of this book, you’ll be equipped to navigate the ever-evolving world of data engineering on Google Cloud, from foundational principles to cutting-edge practices.
What you will learn
- Load data into BigQuery and materialize its output
- Focus on data pipeline orchestration using Cloud Composer
- Formulate Airflow jobs to orchestrate and automate a data warehouse
- Establish a Hadoop data lake, generate ephemeral clusters, and execute jobs on the Dataproc cluster
- Harness Pub/Sub for messaging and ingestion for event-driven systems
- Apply Dataflow to conduct ETL on streaming data
- Implement data governance services on Google Cloud
Who this book is for
Data analysts, IT practitioners, software engineers, or any data enthusiasts looking to have a successful data engineering career will find this book invaluable. Additionally, experienced data professionals who want to start using Google Cloud to build data platforms will get clear insights on how to navigate the path. Whether you’re a beginner who wants to explore the fundamentals or a seasoned professional seeking to learn the latest data engineering concepts, this book is for you.
Table of Contents
- Fundamentals of Data engineering with GCP
- Big Data Capabilities on GCP
- Building a data warehouse in BigQuery
- Build Orchestration for Batch Data Loading Using Cloud Composer
- Building a Data Lake using Dataproc
- Process Streaming Data with Datastream, Pub/Sub and Dataflow
- Visualizing Data for Making Data-Driven Decisions with Looker Studio
- Build machine learning solutions on GCP
- User and Project Management on GCP
- Data Governance in GCP
- Cost Strategy in GCP
- CI/CD on Google Cloud Platform for Data Engineers
- Boost your confidence as a Data Engineer
Editorial Reviews
Review
“This book equips you to create ETL/ELT pipelines using GCP; collect, transform, and visualize data from multiple source types (batch/streaming); and learn about tools that will be very important in your data engineering career. Abundant exercises throughout will facilitate your journey toward mastery.
With this book, you too can emerge as an esteemed data engineer, proficient in harnessing the full potential of the Google Cloud Platform stack. Highly recommended!”
António Vilares, Data Platform Technical Manager at Viator, Tripadvisor
“I particularly appreciate the book’s in-depth coverage of modern GCP tools such as Dataplex and Dataform. Each feature and product is explained in meticulous detail, from setup to implementation, bridging the gap between theory and real-world application. The book demonstrates how to leverage these technologies to solve real-world problems, which is a crucial aspect of effective learning.
Wijaya’s clear and concise writing style ensures that even the most intricate concepts are easy to grasp. This book is an indispensable resource for anyone in the field.”
Sireesha Pulipati, Analytics and BI Lead at Google
“The book reflects the author’s personality: it is thorough and engaging. It’s also written in a way that makes the readers easily understand abstract data engineering concepts, before guiding them into the technical depths of data engineering with Google Cloud. This book is generous with code examples and screenshots, ensuring we can follow along.
I recommend it to software data engineers eager to learn end-to-end data engineering skills in Google Cloud. The book even goes as far as to hand-hold you through advanced practices such as machine learning and stream processing.
Personally, I found the chapter on machine learning the most exciting. I learned to use Google’s Vertex AI to train, evaluate, and deploy an ML model!”
Febiyan Rachman, Data Platform Architect, Pandora
About the Author
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.
