By completing this course, learners will be able to identify Big Data challenges, explain Hadoop’s architecture, configure HDFS for distributed storage, execute MapReduce programs, and apply advanced cluster management techniques. Participants will also develop the ability to validate system health, implement fault tolerance, and integrate Java applications with Hadoop for real-world use cases.
Hadoop: Analyze, Configure & Manage Big Data
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Hadoop: Analyze, Configure & Manage Big Data
This course is part of Hadoop & Big Data Foundations Mastery Course Specialization
Instructor: EDUCBA
Included with 
Gain insight into a topic and learn the fundamentals.
2 weeks to complete
at 10 hours a week
Flexible schedule
Learn at your own pace
What you'll learn
Configure and manage HDFS for distributed data storage.
Execute and optimize MapReduce jobs for large datasets.
Implement fault tolerance and monitor Hadoop cluster health.
Skills you'll gain
Details to know
Shareable certificate
Add to your LinkedIn profile
Recently updated!
November 2025
Assessments
29 assignments
Taught in English
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This course is part of the Hadoop & Big Data Foundations Mastery Course Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
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There are 6 modules in this course
This module introduces learners to the fundamentals of Big Data and the Hadoop ecosystem. It covers the challenges posed by massive datasets, explains the flow of data through HDFS write and read processes, and demonstrates MapReduce basics with the Word Count example to establish a solid foundation.
What's included
14 videos5 assignments
This module dives deeper into Hadoop fundamentals by connecting Big Data concepts to practical scenarios. Learners explore the MapReduce model, gain familiarity with the Cloudera distribution, and use interfaces like HDFS Web UI, HUE, and shell commands for hands-on understanding.
What's included
12 videos5 assignments
This module emphasizes hands-on management of HDFS and integrates Java for real-world applications. Learners practice advanced shell operations, understand the responsibilities of Hadoop administrators, and explore critical HDFS components like FS Image and Secondary NameNode.
What's included
8 videos4 assignments
This module focuses on Hadoop architecture and system setup. It guides learners through HDFS architecture, block placement policy, installation processes, and critical cluster configuration steps such as hostnames, gateways, SSH, and password-less authentication.
What's included
14 videos5 assignments
This module builds expertise in managing Hadoop clusters through detailed configuration tasks. It covers Hadoop’s core files, slave file setup, rack awareness, DFS admin tools, and essential commands for executing and managing MapReduce jobs.
What's included
13 videos5 assignments
This module equips learners with advanced operational skills for managing and maintaining Hadoop clusters. It covers HDFS file operations, checkpointing, safe and maintenance modes, DataNode commissioning, validation, and storage planning considerations.
What's included
13 videos5 assignments
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