An end-to-end analytics project combining Python and Power BI to analyze retail and warehouse sales performance, product performance, supplier contribution, and beverage category trends — transforming raw sales data into actionable business insights.
The Retail Business Performance Dashboard is an interactive business intelligence project built using Python for data analysis and Power BI for visualization. It analyzes retail and warehouse sales performance, product performance, supplier contribution, and beverage category trends to support strategic decision-making.
Retail organizations generate large volumes of sales data across multiple products, suppliers, and categories — without proper analysis this makes it difficult to identify top-selling products, understand supplier contribution to revenue, monitor monthly sales performance, compare retail and warehouse operations, and understand category-wise sales contribution.
The objective was to build a centralized reporting solution: cleaning and validating raw sales data in Python, running exploratory data analysis to surface trends and outliers, and then developing an interactive Power BI dashboard that lets stakeholders monitor sales trends, evaluate suppliers, and compare channels in one place.
The dataset encompasses retail and warehouse sales transaction records, cleaned and validated in Python before being loaded into Power BI for modeling and visualization.
Data fields included:
This project transforms raw retail sales data into a comprehensive Business Intelligence solution. By combining Python-based analysis with Power BI visualizations, the dashboard gives stakeholders a centralized platform to monitor sales performance, evaluate supplier contribution, analyze product demand, and make informed business decisions — from inventory planning and supplier relationships to warehouse optimization and category expansion.
Feel free to reach out for feedback, collaboration, or any data analytics opportunities.