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.