Data Engineering with Google Cloud Platform: A guide to leveling up as a data engineer by building a scalable data, 2nd Edition


Data Engineering with Google Cloud Platform
by Adi Wijaya

English | 2024 | ISBN: 1835080111 | 476 pages | True/Retail PDF EPUB | 66.27 MB


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 invaluable insights into managing and optimizing data resources effectively. Furthermore, 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


Data Engineering with Google Cloud Platform: A guide to leveling up as a data engineer by building a scalable data, 2nd Edition

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