EdX

Building Batch Data Pipelines on Google Cloud (edX)

Offered by Google Cloud,
Building Batch Data Pipelines on Google Cloud (edX)

Developers responsible for designing pipelines and architectures for data processing. Data pipelines typically fall under one of the Extra-Load, Extract-Load-Transform or Extract-Transform-Load paradigms. This course describes which paradigm should be used and when for batch data.

Class Deals by MOOC List - Click here and see EdX's Active Discounts, Deals, and Promo Codes.

Furthermore, this course covers several technologies on Google Cloud for data transformation including BigQuery, executing Spark on Dataproc, pipeline graphs in Cloud Data Fusion and serverless data processing with Dataflow. Learners will get hands-on experience building data pipeline components on Google Cloud using Qwiklabs.
This course is part of the Google Cloud Data Engineer Learning Path Professional Certificate.

What you'll learn

  • Review different methods of data loading: EL, ELT and ETL and when to use what
  • Run Hadoop on Dataproc, leverage Cloud Storage, and optimize Dataproc jobs
  • Build your data processing pipelines using Dataflow
  • Manage data pipelines with Data Fusion and Cloud Composer

Prerequisites:
To benefit from this course, participants should have completed “Google Cloud Big Data and Machine Learning Fundamentals” or have equivalent experience.
Participant should also have:
• Basic proficiency with a common query language such as SQL.
• Experience with data modeling and ETL (extract, transform, load) activities.
• Experience with developing applications using a common programming language such as Python.
• Familiarity with machine learning and/or statistics

Syllabus

  1. Introduction

In this module, we introduce the course and agenda

  1. Introduction to Building Batch Data Pipelines

This module reviews different methods of data loading: EL, ELT and ETL and when to use what

  1. Executing Spark on Dataproc

This module shows how to run Hadoop on Dataproc, how to leverage Cloud Storage, and how to optimize your Dataproc jobs.

  1. Serverless Data Processing with Dataflow

This module covers using Dataflow to build your data processing pipelines.

  1. Manage Data Pipelines with Cloud Data Fusion and Cloud Composer

This module shows how to manage data pipelines with Cloud Data Fusion and Cloud Composer.

  1. Course Summary

Course Summary

  1. Course Resources

PDF links to all modules

Go to Class
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

Machine Learning With Big Data (Coursera) Coursera
University of California, San Diego

Machine Learning With Big Data (Coursera)

Want to make sense of the volumes of data you have collected? Need to incorporate data-driven decisions into your process? This course provides an overview of machine learning techniques to explore, analyze, and leverage data. You will be introduced to tools and algorithms you can use to create machine learning models that learn from data, and to scale those models up to big data problems.

Jun 22nd 2026
5-12 Weeks
Smart Analytics, Machine Learning, and AI on Google Cloud (edX) EdX
Google Cloud

Smart Analytics, Machine Learning, and AI on Google Cloud (edX)

This course covers several ways machine learning can be included in data pipelines on Google Cloud depending on the level of customization required. Incorporating machine learning into data pipelines increases the ability of businesses to extract insights from their data. This course covers several ways machine learning can be included in data pipelines on Google Cloud depending on the level of customization required.

Self Paced
Self-Paced
Building Scalable Java Microservices with Spring Boot and Spring Cloud (Coursera) Coursera
Google Cloud

Building Scalable Java Microservices with Spring Boot and Spring Cloud (Coursera)

"Microservices" describes a software design pattern in which an application is a collection of loosely coupled services. These services are fine-grained, and can be individually maintained and scaled. The microservices architecture is ideal for the public cloud, with its focus on elastic scaling with on-demand resources. In this course, you will learn how to build Java applications using Spring Boot and Spring Cloud on Google Cloud Platform.

Jun 23rd 2026
2 Weeks
Elastic Google Cloud Infrastructure: Scaling and Automation (edX) EdX
Google Cloud

Elastic Google Cloud Infrastructure: Scaling and Automation (edX)

Cloud Solutions Architects, DevOps Engineers. Individuals using Google Cloud to create new solutions or to integrate existing systems, application environments, and infrastructure, with a focus on Compute Engine. This accelerated on-demand course introduces participants to the comprehensive and flexible infrastructure and platform services provided by Google Cloud.

Self Paced
Self-Paced
Data Processing and Analysis with Excel (edX) EdX
Rochester Institute of Technology,RITx

Data Processing and Analysis with Excel (edX)

Learn to use Excel to organize and clean data so it can be manipulated and analyzed. In this course, you will learn how to organize your data within the Microsoft Office Excel software tool. Once organized, we will discuss data cleaning. You will learn how to identify outliers and anomalies in the data, and how to identify and change data-types. Together we will develop a data analysis plan, after which we will apply analysis methods and tools, including exploratory analysis, evaluation of results, and comparison with other findings.

Self Paced
Self-Paced