An interactive Power BI dashboard analyzing Super Store sales performance across US regions, uncovering trends in revenue, profitability, shipping, and customer segments to support data-driven business decisions.
Retail businesses often struggle to identify which regions, categories, and time periods are driving or dragging profitability. This dashboard centralizes sales, profit, and order data into one interactive view — enabling managers to filter by region and instantly surface performance gaps.
- Source: Super Store Sales Dataset (US retail transaction data)
- Period: 2019 – 2020
- Records: ~10,000+ orders across 4 US regions
| Metric | Value |
|---|---|
| Total Orders | 42 |
| Total Sales | 5.46K |
| Total Profit | 8,400 |
| Avg Ship Days | 504 |
- Region filter — Toggle between Central, East, South, and West regions instantly
- Sales by Ship Mode — Standard Class leads at 78K, identifying preferred logistics channels
- Sales by Category — Office Supplies (0.15M) > Furniture (0.11M)
Technology (0.09M)
- Sales by Sub-Category — Chairs, Phones, and Binders are the top 3 revenue drivers
- Profit by State — US map visual highlighting high and low-performing states geographically
- Payment Mode Breakdown — COD (41%), Online (39%), Cards (20%)
- Customer Segment Split — Consumer (48%), Corporate (33%), Home Office (20%)
- Monthly Profit & Sales YOY — Side-by-side 2019 vs 2020 trend lines to track seasonal patterns and growth
- Q4 is the strongest quarter — both profit and sales spike sharply in November–December, indicating seasonal demand
- COD dominates payments at 41%, suggesting an opportunity to push online/card payments for faster cash flow
- Standard Class shipping accounts for the majority of orders — reviewing its cost vs faster shipping modes could improve margins
- Technology has the lowest sales volume among categories but warrants a deeper margin analysis — it may punch above its weight in profitability
- Power BI Desktop — Data modeling, DAX measures, interactive visuals
- Microsoft Excel — Data source and preprocessing
- DAX — Custom KPI calculations and YOY comparisons
| File | Description |
|---|---|
jaja.pbix |
Power BI dashboard file |
superstore_sales_data.csv |
Raw dataset used for analysis |
superstore_dashboard.jpeg |
Dashboard preview screenshot |
- Download the
.pbixfile - Open in Power BI Desktop (free download from Microsoft)
- Use the region buttons at the top to filter all visuals simultaneously
- Hover over charts for detailed tooltips
Abhinav Verma
Aspiring Data & Business Analyst | Power BI · SQL · Excel
📧 abhinavverma03985@gmail.com
🔗 LinkedIn |
GitHub