This project is an interactive Power BI dashboard created to analyze Store sales data.
The dashboard provides an overview of sales performance, quantity, profit, Average Order Value (AOV), customers, states, product categories, sub-categories, and payment methods.
The main objectives of this project are:
- Analyze overall sales performance
- Track total sales, quantity, profit, and Average Order Value
- Identify top customers
- Analyze monthly profit trends
- Identify top-performing states
- Analyze profit by product sub-category
- Understand payment method distribution
- Analyze quantity by product category
- Enable interactive filtering for business analysis
- Power BI Desktop
- Power Query
- DAX
- CSV Dataset
- Data Visualization
Imported the Madhav Store sales dataset into Power BI.
Used Power Query to clean and transform the raw data before analysis.
Prepared the data model and relationships required for analysis.
Created calculations for important business metrics such as:
- Total Sales
- Total Quantity
- Total Profit
- Average Order Value (AOV)
Created an interactive dashboard using KPI cards, charts, and slicers.
The dashboard tracks:
- 💰 Total Sales
- 📦 Total Quantity
- 📈 Total Profit
- 🛒 Average Order Value
The dashboard includes:
- Profit by Month
- Top Customers
- Top States
- Profit by Sub-Category
- Quantity by Payment Mode
- Quantity by Category
A State slicer allows users to filter the dashboard and explore location-specific performance.
This dashboard helps answer questions such as:
- What are the overall sales and profit?
- Which months generate higher or lower profit?
- Who are the top 5 customers?
- Which states contribute significantly to sales?
- Which sub-categories generate higher profit?
- Which payment methods are commonly used?
- Which categories have the highest quantity?