Real-time data pipeline for STEDI Human Balance Analytics using Redis, Kafka, Kafka Connect, and Spark Structured Streaming. Parses customer events, risk events, joins streams, and publishes enriched fall-risk insights to power the live STEDI risk analysis graph.

This project was developed as part of UE20CS343 - Database Technologies to build a real-time data streaming pipeline using Apache Kafka and Spark Structured Streaming. It simulates ingesting San Francisco crime data into Kafka, processing it with Spark, and performing aggregations and stream-table joins.

A sandbox environment designed to simulate a pseudo-distributed Hadoop cluster with integrated Apache Spark and Kafka components. It allows developers to prototype and experiment with big data workflows, test distributed computing patterns, and explore cluster behavior in a contained virtual setup.