Overview

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Build practical Big Data analytics skills by processing real-world sensor datasets with Hadoop MapReduce, Apache Pig, and Apache Hive. You’ll begin by exploring how sensor data is collected and structured, then preprocess JSON files and apply Big Data principles for efficient data handling. Using MapReduce, you’ll analyze demographic and social datasets through use cases involving gender ratios, income tax predictions, and child labor analysis. Next, you’ll use Apache Pig functions, relations, and reusable scripts to simplify data processing. You’ll create data flows and apply filtering, grouping, and aggregation techniques to uncover patterns and calculate meaningful ratios. Finally, you’ll explore Hive architecture and features, execute SQL-like Hive queries on historical and JSON-based datasets, and evaluate results that can support government, business, strategic, and policy decisions. Designed for learners who want hands-on experience with Big Data processing and analysis, this project-based course brings MapReduce, Pig, and Hive together in one structured workflow. You’ll practice designing data flows, troubleshooting errors, and transforming raw sensor data into meaningful reports and actionable insights. Enroll to develop practical skills for analyzing large-scale data and supporting evidence-based decision-making.

Syllabus

Foundations of Sensor Data & MapReduce
- This module introduces the foundations of sensor data analysis and the principles of Big Data processing. Learners explore how raw data is collected, structured, and converted into usable formats, followed by an introduction to Hadoop MapReduce. The module covers real-world use cases including demographic analysis, income tax prediction, and child labor detection, helping learners understand how analytics can drive social and economic insights.
Sensor Data Processing with Pig
- This module focuses on Apache Pig, a high-level data flow language used for simplifying Big Data processing. Learners gain practical skills in Pig functions, relations, and data flow management while reducing the complexity of coding compared to MapReduce. Through hands-on use cases, students practice grouping, filtering, and aggregating sensor data to uncover patterns and generate meaningful ratios for analysis.
Advanced Analysis with Hive
- This module explores Apache Hive, a data warehouse tool that enables SQL-like querying of large datasets. Learners examine Hive’s key features, its ability to query JSON data, and how it empowers non-programmers to analyze massive datasets efficiently. By completing Hive-based use cases, learners discover how to transform raw data into meaningful reports that support government and business decision-making.