Data Engineering on Google Cloud Platform Course

Get proficient in extracting business insights from vast datasets with the help of BigQuery . Enroll in Data Engineering on Google Cloud course to design and build secure and effective data processing systems. This is a 4-day course designed for someone who has a basic understanding of Google Cloud's Big Data and ML capabilities, data modelling and ETL processes. Having familiarity with programming languages would be an added advantage to get the best out of this course.

Your learning method

Virtual Instructor-Led Training

$ 2,475

Virtual Instructor-Led Training

4 Days (32 Hours)

Expand your LightWave skills and learn advanced techniques for creating 3D animations and visualizations. Produce high-quality 3D content for various purposes.

Course Objectives

Design and build data processing systems on Google Cloud
Process batch and streaming data by implementing autoscaling data pipelines on Dataflow
Derive business insights from extremely large datasets using BigQuery
Leverage unstructured data using Spark and ML APIs on Dataproc
Enable instant insights from streaming data

Download course details

Upcoming Schedules

Date	Time		Enroll
May 13 - May 16, 2025	9:00 AM - 5:00 PM CST
Jul 15 - Jul 18, 2025	9:00 AM - 5:00 PM CST
Sep 16 - Sep 19, 2025	9:00 AM - 5:00 PM CST
Nov 18 - Nov 21, 2025	9:00 AM - 5:00 PM CST

Exam and Certification

Exam

PDE: Google Cloud Certified Professional Data Engineer

Certification

Google Cloud Certified Professional Data Engineer

Who Should Attend?

Data Engineer

Course Prerequisites

Required

Basic proficiency with common query language such as SQL

Developing applications using a common programming language such Python

Familiarity with Machine Learning and/or statistics

Experience with data modeling, extract, transform, load activities

Course Outline

Introduction to Data Engineering

Explore the role of a data engineer
Analyze data engineering challenges
Introduction to BigQuery
Data lakes and data warehouses
Transactional databases versus data warehouses
Partner effectively with other data teams
Manage data access and governance
Build production-ready pipelines
Review Google Cloud customer case study
Understand the role of a data engineer
Discuss benefits of doing data engineering in the cloud
Discuss challenges of data engineering practice and how building data pipelines in the cloud helps to address these
Review and understand the purpose of a data lake versus a data warehouse, and when to use which
Lab: Using BigQuery to do Analysis

Building a Data Lake

Building a Data Warehouse

Introduction to Building Batch Data Pipelines

Executing Spark on Dataproc

Serverless Data Processing with Dataflow

Manage Data Pipelines with Cloud Data Fusion and Cloud Composer

Introduction to Processing Streaming Data

Serverless Messaging with Pub/Sub

Dataflow Streaming Features

High-Throughput BigQuery and Bigtable Streaming Features

Advanced BigQuery Functionality and Performance

Introduction to Analytics and AI

Prebuilt ML Model APIs for Unstructured Data

Big Data Analytics with Notebooks

Production ML Pipelines

Custom Model Building with SQL in BigQuery ML

Custom Model Building with AutoML

Frequently Asked Questions

What is this Data Engineering on the Google Cloud Platform Course about?

This Data Engineering on the Google Cloud Platform Course teaches you to design, build, and manage effective data processing systems on Google Cloud, extracting business insights using BigQuery, Cloud Bigtables, and Cloud SQL.

Data Engineering on Google Cloud