1. Overview:
This project focuses on sales performance analysis using the Superstore dataset from Kaggle. It includes data cleaning, KPI tracking, and interactive dashboards to uncover sales trends, profitability insights, and regional performance.
The dashboard is fully interactive with slicers, enabling dynamic filtering by various dimensions such as category, sub-category, state, and year.
2. Dataset:
Source: Kaggle – Superstore Dataset
Data Type: Sales transaction data with details on order date, region, category, sub-category, sales, profit, and more.
3. Objective:
Analyze sales trends over time.
Identify top-performing products, categories, and regions.
Track profitability and gross margin performance.
Provide actionable insights through an interactive Excel dashboard.
4. Key Metrics (KPI Cards):
Total Sales
Total Profits
Total Orders
Gross Margin (%)
5. Dashboard Features & Visuals:
Charts Included:
Combo Chart: Sales vs Months (Columns) & Moving Averages (Line)
Combo Chart: Sales vs Months (Columns) & MoM % Change (Line)
Combo Chart: Sales vs Sub-category (Line) & Profits vs Sub-category (Line)
Donut Chart: Sales by Year
Pie Chart: Sales by Category
Map Chart: Sales Percentage by Region
6. Insights (Dynamic via Slicers):
Highest Sales Month: November
Top State: California (highest in both sales & profits)
MoM Change: -37.05% in February compared to the previous month (possible post-holiday drop)
Gross Margin: 12% (below usual levels due to huge discounts)
Top Product: Phones (14% of total revenue)
In 2017 Most Profitable Product: Copiers (low sales but high profit margin)
7. Tools Used:
Microsoft Excel – for data cleaning, pivot tables, dashboard creation, and visualizations.
8. File Structure:
Superstore_Analytics.xlsx – Main Excel file with:
Sheet 1: Cleaned Data
Sheet 2: KPI Calculations
Sheet 3: Dashboard
Sheet 4: Insights
9. How to Use:
Download the Excel file from this repository.
Open in Microsoft Excel (desktop) for full interactivity.
Use slicers to filter data and see KPIs, charts, and insights update dynamically.
10. References:
Kaggle Superstore Dataset: https://www.kaggle.com/datasets