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Engineering Data Ecosystems: Pipelines, ETL, Spark
Master the fundamentals of modern data ecosystems: from data pipelines and ETL processes to big data handling with Apache Spark for effective data engineering.
Course Cost
Free course
Beginner
Skill Level
3 Hours
Self-paced lessons
This foundational course explores the essential components of modern data ecosystems, focusing on data pipelines, ETL processes, and Apache Spark for big data handling. Designed for aspiring data engineers and IT professionals, it covers fundamental tools and technologies driving today's data-driven decision-making. Through comprehensive lessons on data pipeline construction, ETL workflow management, and Spark applications, participants gain practical knowledge in large-scale data processing.
English
What you'll learn
Identify and describe the components and importance of data ecosystems
Understand the basic structure and function of data pipelines
Recognize the steps involved in ETL workflows
Gain introductory knowledge of big data processing
Master the fundamentals of Apache Spark applications
Implement scalable data solutions
Skills you'll gain
This course includes:
61 Minutes PreRecorded video
1 assignment, 2 discussion prompts
Access on Mobile, Tablet, Desktop
FullTime access
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There is 1 module in this course
This comprehensive course introduces the fundamentals of data ecosystems and engineering. Students learn about the construction and management of data pipelines, the implementation of ETL (Extract, Transform, Load) workflows, and big data processing using Apache Spark. The curriculum covers essential aspects of data ecosystem design, tools and technologies for data pipeline management, and practical applications of Spark in large-scale data processing, providing a solid foundation for aspiring data engineers.
Engineering Data Ecosystems: Pipelines, ETL, Spark
Module 1 · 3 Hours to complete
Fee Structure
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Frequently asked Questions
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