Data Engineering: Pipelines, ETL, Hadoop
Learn to build robust data pipelines, implement ETL processes, and master Hadoop ecosystem for large-scale data processing.
Course Cost
Free course
Intermediate
Skill Level
4 Hours
Self-paced lessons
This comprehensive course teaches data engineering fundamentals, focusing on building scalable data pipelines and ETL processes. Students learn to extract data from various sources, transform it effectively, and load it into data warehouses using industry-standard tools. The curriculum covers the Hadoop ecosystem, including HDFS, MapReduce, Hive, Pig, and Spark, preparing learners to handle big data challenges in real-world scenarios.
What you'll learn
Analyse the architecture and components of data pipelines
Implement robust ETL processes for scalability
Analyze big data challenges using Hadoop ecosystem tools
Design and execute data processing solutions
Skills you'll gain
This course includes:
70 Minutes PreRecorded video
1 assignment,2 discussion prompts
Access on Mobile, Tablet, Desktop
FullTime access
Shareable certificate
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There is 1 module in this course
This comprehensive data engineering course focuses on building robust data pipelines, implementing ETL processes, and mastering the Hadoop ecosystem. Students learn to analyze pipeline architecture, implement scalable ETL processes, and handle big data challenges. The curriculum covers essential Hadoop tools including HDFS, MapReduce, Hive, Pig, and Spark, providing hands-on experience in extracting, transforming, and loading data from various sources into data warehouses or big data platforms.
Data Engineering: Pipelines, ETL, Hadoop
Module 1 · 4 Hours to complete
Fee Structure
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Faculties
These are the expert instructors who will be teaching you throughout the course. With a wealth of knowledge and real-world experience, they're here to guide, inspire, and support you every step of the way. Get to know the people who will help you reach your learning goals and make the most of your journey.
Frequently asked Questions
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