Coffee Sales Analysis

SQL : Analyzed total revenue per coffee type, identified frequent buyers for targeted

marketing, and pinpointed peak sales hours to optimize resources.

Python : Loaded and explored large datasets, analyzed daily sales trends, identified top

coffee products by revenue, visualized peak sales hours, and profiled high-value

customers for retention.

Power BI : Developed a sales trend line, heatmap of peak sales by coffee type, and

customer purchase matrix. Implemented forecasting and dynamic time-range analyses for

deeper revenue insights.