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
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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
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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.
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 videos•Total 105 minutes
- Introduction to Log Processing•8 minutes
- Summarizing Log Files•6 minutes
- MapReducing Programme•9 minutes
- Execute MapReduce Program•9 minutes
- Big Data Technology•10 minutes
- Executing Big Data Tool•10 minutes
- Writing Map Reduce Program•7 minutes
- Array List Searching•7 minutes
- Processing Files In Map Reduce•6 minutes
- Conclusion•7 minutes
- Introduction to Sales Data Analysis Using Hadoop- HDFS•10 minutes
- Working with Problem Statement 1•8 minutes
- Working with Problem Statement 2•8 minutes
4 assignments•Total 60 minutes
- Building the Foundation – Log & Sales Data Projects•30 minutes
- Understanding Log Data Processing in Hadoop•10 minutes
- Exploring Big Data Tools and File Operations•10 minutes
- Beginning Sales Data Analysis Using Hadoop•10 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 videos•Total 77 minutes
- Working with Problem Statement 3•9 minutes
- Working with Problem Statement 4•7 minutes
- Working with Problem Statement 5•6 minutes
- Introduction to Tourism Survey Analysis Using HDFS•10 minutes
- Average of Money Spend By Tourist in our Country•7 minutes
- Join Country and Nationality•8 minutes
- Total no. of Tourist Less than 18•7 minutes
- Change the Country Name Column•6 minutes
- Number of Males from Australia•7 minutes
- Tourism Survey General Detail and Spending Details•10 minutes
4 assignments•Total 60 minutes
- Advancing Data Analysis – Sales & Tourism Projects•30 minutes
- Solving Complex Sales Data Problems with MapReduce•10 minutes
- Tourism Data Analytics and Insights•10 minutes
- Advanced Filtering and Transformation in Tourism Analysis•10 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 videos•Total 51 minutes
- Introduction to Faculty Data Management Using HDFS•7 minutes
- Education Industry•6 minutes
- Adding New Column in Faculty Database Management•8 minutes
- Changing Column Name and Data Type•7 minutes
- Drop Column From Table and Add New Column•9 minutes
- Introduction to E-Commerce Sales Analysis Using Hadoop•6 minutes
- Customer Detail not from USA•8 minutes
4 assignments•Total 80 minutes
- Managing and Transforming Educational Data•30 minutes
- Faculty Data Management Using HDFS•10 minutes
- Modifying Faculty Database Structures•30 minutes
- Introduction to E-Commerce Data Analysis•10 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.
What's included
10 videos4 assignments
10 videos•Total 71 minutes
- Customer Detail Account Created After 2009•9 minutes
- Customer Details whose Sales are Less than 3600$•7 minutes
- Details of Customer Name Anushka•6 minutes
- Part time Employee using Salary Analysis•7 minutes
- Details of Administrative Assistance•6 minutes
- Data Sets in Ascending Order•7 minutes
- Job Title for Each Department•8 minutes
- Changing Name to Employee Name•7 minutes
- Total number of Employee in Hourly Basis•7 minutes
- Annual Salary Taken By Finance Department•8 minutes
4 assignments•Total 60 minutes
- Real-World Business Analytics – E-Commerce & Salary Projects•30 minutes
- Exploring Customer Insights in E-Commerce Data•10 minutes
- Salary Analysis and Employee Data Operations•10 minutes
- Advanced Salary Analytics and Department Insights•10 minutes
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