This project presents a detailed sales performance analysis using the popular SuperStore dataset, built in Power BI with dynamic visualizations and business insights.
To analyze historical sales, profit, and customer behavior data across different categories and regions to uncover patterns, identify problem areas, and guide decision-making through an interactive dashboard.
- Source: [SuperStore Dataset (Kaggle)]
- Records: 9,994 rows
- Fields include: Order Date, Region, Segment, Category, Sub-Category, Sales, Profit, Quantity, and Discount
- Power BI – Dashboard creation, visual design, interactivity
- Power Query – Data cleaning, transformation, table relationships
- DAX (Data Analysis Expressions) – Calculated fields, time-based metrics
- Excel – Initial inspection and validation
- 📈 Sales & Profit Analysis by Region, Category, Sub-Category
- 🔎 Profitability Heatmap to identify underperforming segments
- 📊 Dynamic Filters & Slicers to slice by Region, Segment, Category
- 📆 Time Series Breakdown of monthly sales & profit trends
- ✅ KPIs at a Glance: Total Sales, Profit, Discount Rate, Average Order Value
- The Central region generated the highest overall profit, while South showed high sales but low profit margins
- Tables and Bookcases in Furniture were loss-leading products despite strong sales volume
- High discounts in certain categories significantly impacted profit — indicating opportunities for pricing optimization
- Seasonal spikes observed in Q4, especially during November–December
This project demonstrates the ability to:
- Build end-to-end business intelligence dashboards
- Extract actionable insights from retail data
- Communicate findings using interactive, visual storytelling
- Translate raw data into decisions that drive business impact
📫 LinkedIn – yashdtu
📂 Portfolio Projects
“A dashboard is only as valuable as the decisions it empowers.”