Online Shopping Behavior Analysis

This project analyzes online shopping behavior between men and women using a Flask web application and real-time data streaming with Kafka. The application serves as a live dashboard that visualizes consumer behavior by continuously consuming and processing data.

Key Features

• Real-Time Data Processing: Utilizes Kafka to consume messages that contain shopping behavior data, distinguishing between male and female shopping patterns.
• WebSocket Integration: Implements Flask-SocketIO to establish real-time communication between the server and client, ensuring instantaneous updates on shopping behavior statistics.
• Data Visualization: Emits processed data to the front end for live display, allowing users to observe trends and insights regarding male and female shopping habits.
• Background Processing: Runs a separate background thread to handle incoming Kafka messages, processing the data and emitting results to connected clients.

Technologies Used

• Flask: For creating the web application.
• Flask-SocketIO: For real-time bidirectional communication.
• Kafka: For streaming data consumption.
• HTML/CSS: For front-end rendering.