Superstore Sales Dashboard

Abstract

1. Introduction

The dashboard features region-based filtering (Central, East, South, West) and displays key KPIs alongside rich visualizations for data-driven decision making.

An interactive Power BI Sales Dashboard built on the popular Superstore dataset, providing comprehensive insights into sales, profit, shipping, and regional performance across four US regions.

2. Objective

📊 An interactive Power BI dashboard analyzing Super Store sales data (2011–2014) across 4 US regions — featuring KPIs, monthly trends, profit forecasting, category breakdowns, and geographic visualizations built with DAX & Power Query.

This project demonstrates how modern tools can be applied to a real-world Data Science problem.

3. Key Features / Modules

• Region Filters — Toggle between Central, East, South, and West with one click
• Sales by Segment — Donut chart: Consumer (~50%), Corporate (~31%), Home Office (~19%)
• Sales by Discount — Discount tier distribution across all orders
• Sales by Region — Regional contribution breakdown
• Sales by Month — Multi-year (2011–2014) area/line chart
• Profit by Month — Year-over-year monthly profit trends
• Sales by Ship Mode — Standard Class, Second Class, First Class, Same Day
• Sales by Category — Technology, Furniture, Office Supplies
• Sales by Sub-Category — Tables, Storage, Supplies
• Profit & Sales by State — Bing Maps visual with geographic drill-down

4. Technology Stack

5. System Requirements

General requirements for this technology stack — check the README for exact versions.

• See the project README for exact requirements
• Git (to clone the repository)

6. Installation & Setup

git clone https://github.com/harshitaswal04/superstore-sales-dashboard.git
cd superstore-sales-dashboard

1. Clone this repository
2. Open the Power BI file
3. Install Power BI Desktop (free)
4. Open sales_powerbi.pbix
5. Refresh the data (if needed)
6. Go to Home → Transform Data
7. Update the Superstore.csv file path in Power Query
8. Click Close & Apply

git clone https://github.com/harshitaswal04/superstore-sales-dashboard.git
   cd superstore-sales-dashboard

Full setup instructions are in the project README.

7. Future Enhancements

Suggested extensions you can add to make this your own project.

• Turn the analysis into an interactive dashboard
• Automate data refresh with a scheduled job
• Add a predictive model on top of the analysis

8. Viva / Review Questions

Common questions examiners ask for projects in this domain.

1. What is the source of the dataset and how was missing data handled?
2. Which exploratory analysis steps revealed the most useful insight?
3. Why were these particular charts chosen to present the data?
4. Which statistical or ML technique supports the conclusions?
5. How could the analysis be automated or refreshed with new data?

9. Source Code & License

This project is developed by harshitaswal04 and published on GitHub under the MIT License. Please follow the license terms and credit the original author when you use or modify this code.