Project Details

Big Data / Web Application 2025

Customer Behavior Analysis (Big Data)

This was the capstone project for the Big Data course at Samsung Innovation Campus (SIC). The goal was to process a large e-commerce transaction dataset to find insights into customer behavior and visualize the results on a web dashboard.

Python Pandas Flask Matplotlib Big Data

Technical Description & Role

As the **Data Analyst & Python Developer**, I was primarily responsible for data processing and visualization.

The project consisted of two main parts: a Python script for analysis and a Flask web application for display.

Data Processing: Used the **Pandas** library (Python) to read and clean a large dataset (millions of rows) from a CSV file. Performed merge, group by, and aggregation operations to extract information.
Analytics: Analyzed key metrics such as: Total revenue over time, best-selling products, customer segmentation (RFM - Recency, Frequency, Monetary), and repurchase rates.
Visualization: Used **Matplotlib** and **Seaborn** libraries to create charts (line, bar, pie) to describe the insights found.
Web Dashboard Development: Built a simple website using **Flask** (Python Web Framework). Used a template engine (like Jinja2) and Bootstrap to create a dashboard displaying the charts and analytical figures in an intuitive, friendly way.