PulseSense: Real-Time Big Data Sentiment Analytics

PulseSense, a real-time big data sentiment analytics system.

PulseSense, a real-time big data sentiment analytics system. It is offered as a reference project: a complete, worked example of how a system like this is designed, built and evaluated, so that a developer can study it, run it and learn from it.

It suits learners who want to turn raw data into decisions: collecting and cleaning data, exploring it, modelling it and presenting the findings in a dashboard or report.

The main parts are real-time processing of incoming data, a dashboard with charts and filters, data collection and cleaning, exploratory analysis and feature building, and modelling and validation. The reference build uses Apache Kafka, Apache Spark, NLTK, Python, and Pandas, with a clear project structure, setup instructions and sample data so that it can be run and extended.