Introduction to Data Engineering on Google Cloud
Learn data engineering fundamentals on Google Cloud. Master data pipelines, automation, and core Google Cloud components.
Learn data engineering fundamentals on Google Cloud. Master data pipelines, automation, and core Google Cloud components.
This comprehensive course introduces data engineering on Google Cloud, covering the roles and responsibilities of data engineers and how they align with Google Cloud offerings. You'll learn about data engineering tasks, core components, and various data pipeline patterns including extract-load, extract-load-transform (ELT), and extract-transform-load (ETL). The course also covers data replication, migration, and automation techniques using Google Cloud tools and services. Through hands-on labs and quizzes, you'll gain practical experience with BigQuery, Datastream, BigLake, Dataform, Dataproc, and Cloud Run, preparing you to address real-world data engineering challenges.
Instructors:
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What you'll learn
Understand the role of a data engineer
Identify data engineering tasks and core components used on Google Cloud
Create and deploy data pipelines of varying patterns on Google Cloud
Utilize various automation techniques on Google Cloud
Master key Google Cloud tools for data engineering (BigQuery, Datastream, BigLake, etc.)
Learn data replication and migration strategies
Skills you'll gain
This course includes:
61 Minutes PreRecorded video
6 quizzes, 6 hands-on labs
Access on Mobile, Tablet, Desktop
FullTime access
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There are 8 modules in this course
This course provides a comprehensive introduction to data engineering on Google Cloud. It covers the fundamental concepts, tools, and techniques used by data engineers to manage and process data at scale. The curriculum is structured into modules that progressively build knowledge, starting with the basics of data engineering tasks and components, and advancing to complex topics like data pipeline patterns and automation techniques. Throughout the course, students will learn about various Google Cloud services and how they fit into the data engineering ecosystem. Hands-on labs provide practical experience with key tools like BigQuery, Datastream, BigLake, and Dataform. By the end of the course, learners will have a solid foundation in data engineering principles and practices, specifically tailored to the Google Cloud environment.
Course Introduction
Module 1 · 2 Minutes to complete
Data Engineering Tasks and Components
Module 2 · 2 Hours to complete
Data Replication and Migration
Module 3 · 1 Hours to complete
The Extract and Load Data Pipeline Pattern
Module 4 · 1 Hours to complete
The Extract, Load, and Transform Data Pipeline Pattern
Module 5 · 1 Hours to complete
The Extract, Transform, and Load Data Pipeline Pattern
Module 6 · 2 Hours to complete
Automation Techniques
Module 7 · 1 Hours to complete
Course Summary
Module 8 · 10 Minutes to complete
Fee Structure
Payment options
Financial Aid
Instructor
Empowering Businesses with Expert Training from Google Cloud
The Google Cloud Training team is tasked with developing, delivering, and evaluating training programs that enable our enterprise customers and partners to effectively utilize our products and solutions. Google Cloud empowers millions of organizations to enhance employee capabilities, improve customer service, and innovate for the future using cutting-edge technology built specifically for the cloud. Our products are designed with a focus on security, reliability, and scalability, covering everything from infrastructure to applications, devices, and hardware. Our dedicated teams are committed to helping customers successfully leverage our technologies to drive their success.
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