FoodHub is a data analytics project designed to analyze customer behavior and operational performance on a food delivery platform. I developed the analysis using Python and modern data analysis techniques.
First, I explored and cleaned the FoodHub dataset containing customer orders, restaurant information, and delivery details. Then, I performed exploratory data analysis and engineered insights that highlight ordering patterns, popular cuisines, and customer preferences.
Next, I used data visualization and statistical analysis to evaluate restaurant performance, order trends, and delivery efficiency.
In addition, I identified key factors that influence customer ordering behavior and platform activity.
Overall, the FoodHub project demonstrates how data analysis can transform raw transactional data into actionable insights that support better decision making in food delivery platforms.