This Power BI project explores and visualizes the sales performance of a retail superstore. It uncovers meaningful patterns across product categories, customer segments, regions, and time periods to support smarter business decisions.
The goal of this project is to derive actionable insights from historical sales data using interactive dashboards. It aims to help improve:
- Inventory planning
- Marketing strategy
- Regional sales performance
- Customer segmentation
- 📆 Sales Trends: December recorded the highest sales in 2020, followed by November and October.
- 👤 Customer Segments: Consumer segment contributed 54% of total sales, while Corporate contributed 30%.
- 🗂️ Top Categories: Office Supplies ranked highest, followed by Technology and Furniture.
- 🚚 Shipping Methods: Standard class shipping was the most frequently used method.
- 📊 Top Products: Phones led sales at nearly 25%, followed by Chairs at 13.75%.
- KPI Cards: Total Sales, Profit, Quantity, Discounts
- Time-based visualizations (monthly/seasonal)
- Region-wise and category-wise breakdowns
- Interactive slicers for dynamic filtering
- Microsoft Power BI
- Power Query Editor
- DAX (Data Analysis Expressions)
- Superstore Dataset (Excel)
Darshan Patil