This project is part of the Future Interns Data Science & Analytics track (DS).
The objective of this task is to analyze business sales data and create a professional dashboard that helps businesses understand their performance and identify growth opportunities.
The analysis was performed using the Superstore dataset and visualized using Power BI.
- Power BI
- Microsoft Excel / CSV Dataset
- GitHub for project documentation
- Superstore Sales Dataset
- Contains information on:
- Orders
- Sales
- Profit
- Products
- Categories
- Regions
- Order Dates
The dashboard provides insights into:
- Total Sales
- Total Profit
- Profit Margin
- Total Orders
- Sales trend over time (Month-Year)
- Sales by Category
- Profit by Region
- Top 5 Products by Sales
- Interactive filters for:
- Region
- Category
- Year
- Technology category generates the highest sales, making it the top revenue contributor.
- West region shows the highest profit, indicating strong performance in that market.
- Sales show seasonal fluctuations, with peaks in certain months, suggesting demand patterns.
- A small number of products contribute significantly to total revenue, indicating high-performing products.
- Some regions generate lower profit compared to sales, indicating possible cost or discount issues.
- Focus marketing and inventory efforts on high-performing products to maximize revenue.
- Expand business strategies in the West region, as it delivers strong profitability.
- Improve pricing or cost control strategies in low-profit regions.
- Plan promotional campaigns during high-demand months to boost sales further.
- Analyze underperforming categories and optimize product mix.
Sales_Performance_Dashboard.pbix– Power BI dashboard filesuperstore.csv– Dataset useddashboard_overview.png– Full dashboard screenshotdashboard_filtered.png– Example filtered view
Anushka Baidya
B.Tech CSE | Data Science & Analytics Intern