Overview

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Master practical Hadoop data analytics through project-based experience with HDFS, MapReduce, Apache Pig, and Apache Hive. You’ll learn to clean, structure, transform, query, and optimize large-scale datasets while building reliable distributed data workflows. Working through log processing, sales, tourism surveys, faculty records, e-commerce, and employee salary projects, you’ll apply Hadoop tools to real business and analytical challenges. You’ll process streaming logs, aggregate sales data, join spending and demographic datasets, design and modify Hive schemas, manage distributed storage, and analyze customer and salary trends. Designed for data engineers, analysts, and IT professionals, this course develops practical skills in data cleaning, schema design, filtering, aggregation, query optimization, workflow automation, and report generation. By the end, you’ll be able to build and execute end-to-end Hadoop workflows, extract actionable insights from diverse datasets, and support business, tourism, e-commerce, and HR decisions. What makes this course distinctive is its integrated, project-driven approach. Instead of studying Hadoop tools separately, you’ll use MapReduce, Pig, Hive, and HDFS together across multiple realistic scenarios, connecting technical concepts with professional application.

Syllabus

Building the Foundation – Log & Sales Data Projects
- 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.
Advancing Data Analysis – Sales & Tourism Projects
- 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.
Managing and Transforming Educational Data
- 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.
Real-World Business Analytics – E-Commerce & Salary Projects
- 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.