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Hadoop Projects: Analyze & Optimize Big Data

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Hadoop Projects: Analyze & Optimize Big Data

This course is part of Hadoop Big Data Analytics & Projects Mastery Specialization

Instructor: EDUCBA

Included with

Learn more

4 modules

Gain insight into a topic and learn the fundamentals.

1 week to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

4 modules

Gain insight into a topic and learn the fundamentals.

1 week to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

What you'll learn

Process and optimize large datasets using Hadoop tools.
Apply MapReduce, Pig, and Hive in real-world data projects.
Build scalable data workflows for analytics and reporting.

Skills you'll gain

Tools you'll learn

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

16 assignments

Taught in English

91% of learners achieved a positive career outcome

See how employees at top companies are mastering in-demand skills

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Build your subject-matter expertise

This course is part of the Hadoop Big Data Analytics & Projects Mastery Specialization

When you enroll in this course, you'll also be enrolled in this Specialization.

Learn new concepts from industry experts
Gain a foundational understanding of a subject or tool
Develop job-relevant skills with hands-on projects
Earn a shareable career certificate

There are 4 modules in this course

By the end of this course, learners will be able to analyze, transform, and optimize large-scale datasets using Hadoop’s distributed ecosystem. They will gain hands-on experience with MapReduce, Pig, and Hive across multiple real-world projects, including log processing, sales analytics, tourism survey insights, faculty data management, e-commerce performance, and salary analysis.

This course emphasizes practical implementation over theory, guiding learners step-by-step through data cleaning, schema design, query optimization, and report generation in a cloud-scale environment. Through integrated projects, learners will learn how to build, execute, and automate data workflows while ensuring reliability and scalability in HDFS. Unlike traditional Hadoop courses, this program delivers a comprehensive, project-driven learning path, helping participants bridge the gap between conceptual understanding and professional application. Ideal for data engineers, analysts, and IT professionals, this course empowers learners to confidently apply Hadoop tools in solving complex business and analytical challenges across industries.

Module details

This module introduces learners to the core principles of Hadoop-based data processing through log and sales data projects. Learners will explore how to clean, process, and analyze streaming log files using MapReduce, Pig, and Hive. The module builds essential technical foundations in distributed file handling and practical data management workflows, setting the stage for advanced Hadoop applications.

What's included

13 videos4 assignments

13 videosTotal 105 minutes

Introduction to Log Processing8 minutes
Summarizing Log Files6 minutes
MapReducing Programme9 minutes
Execute MapReduce Program9 minutes
Big Data Technology10 minutes
Executing Big Data Tool10 minutes
Writing Map Reduce Program7 minutes
Array List Searching7 minutes
Processing Files In Map Reduce6 minutes
Conclusion7 minutes
Introduction to Sales Data Analysis Using Hadoop- HDFS10 minutes
Working with Problem Statement 18 minutes
Working with Problem Statement 28 minutes

4 assignmentsTotal 60 minutes

Understanding Log Data Processing in Hadoop10 minutes
Exploring Big Data Tools and File Operations10 minutes
Beginning Sales Data Analysis Using Hadoop10 minutes
Building the Foundation – Log & Sales Data Projects30 minutes

This module advances learners’ analytical and problem-solving skills through real-world sales and tourism survey projects. By leveraging Hadoop’s distributed ecosystem, learners will gain hands-on experience using MapReduce, Hive, and Pig to aggregate, join, and filter multi-source datasets for business intelligence and demographic insights.

What's included

10 videos4 assignments

10 videosTotal 77 minutes

Working with Problem Statement 39 minutes
Working with Problem Statement 47 minutes
Working with Problem Statement 56 minutes
Introduction to Tourism Survey Analysis Using HDFS10 minutes
Average of Money Spend By Tourist in our Country7 minutes
Join Country and Nationality8 minutes
Total no. of Tourist Less than 187 minutes
Change the Country Name Column6 minutes
Number of Males from Australia7 minutes
Tourism Survey General Detail and Spending Details10 minutes

4 assignmentsTotal 60 minutes

Solving Complex Sales Data Problems with MapReduce10 minutes
Tourism Data Analytics and Insights10 minutes
Advanced Filtering and Transformation in Tourism Analysis10 minutes
Advancing Data Analysis – Sales & Tourism Projects30 minutes

This module focuses on educational and faculty data management projects using Hadoop’s distributed storage and processing tools. Learners will master schema design, data transformation, and optimization in Hive and Pig while enhancing database management efficiency through structural modifications and automation.

What's included

7 videos4 assignments

7 videosTotal 51 minutes

Introduction to Faculty Data Management Using HDFS7 minutes
Education Industry6 minutes
Adding New Column in Faculty Database Management8 minutes
Changing Column Name and Data Type7 minutes
Drop Column From Table and Add New Column9 minutes
Introduction to E-Commerce Sales Analysis Using Hadoop6 minutes
Customer Detail not from USA8 minutes

4 assignmentsTotal 80 minutes

Faculty Data Management Using HDFS10 minutes
Modifying Faculty Database Structures30 minutes
Introduction to E-Commerce Data Analysis10 minutes
Managing and Transforming Educational Data30 minutes

The final module integrates real-world Hadoop use cases in e-commerce and employee salary analytics. Learners will apply distributed querying, filtering, and aggregation techniques to gain actionable insights from diverse data sources. The module emphasizes end-to-end analysis and reporting within Hadoop’s scalable architecture.