A Power BI dashboard designed to analyze sales performance, profitability, regional performance, product performance, and category-level sales trends for 2024–2025.
Tool: Power BI Desktop | Data: 12,000 Sales Records | Period: 2024–2025
The objective of this project is to provide an interactive view of sales performance and profitability using Power BI.
The dashboard helps users:
- Monitor total sales and profit
- Evaluate overall profit margin
- Track order volume
- Analyze monthly sales trends
- Compare sales performance across regions
- Identify high-performing product categories
- Identify the top 10 products by sales
- Filter results by year, region, customer segment, and product category
- Power BI Desktop – Dashboard development and visualization
- Power Query – Data cleaning and transformation
- DAX – Calculated measures and business metrics
- Power BI Data Model – Relationships and data modeling
- Git & GitHub – Project version control and portfolio sharing
The project uses a sales dataset containing 12,000 sales records covering the period 2024–2025.
The Power BI model consists of the following tables:
- Sales – Transaction-level sales data
- Products – Product and category information
- Customers – Customer and segment information
- Salespersons – Salesperson information
- Regions – Regional information
- Date – Date dimension used for time-based analysis
The dataset was cleaned and transformed using Power Query before building the data model and dashboard.
The dataset was prepared in Power Query before creating the dashboard.
Key preparation steps included:
- Removed unnecessary and duplicate records
- Checked and handled missing values
- Corrected data types
- Standardized date fields
- Validated numerical columns such as quantity, price, discount, and cost
- Created a dedicated Date table for time-based analysis
- Created relationships between the Sales table and supporting dimension tables
- Verified the final data model before creating DAX measures
The Power BI model follows a simple star-schema structure, with the Sales table serving as the central fact table and the remaining tables acting as supporting dimensions.
SalesProductsCustomersSalespersonsRegionsDate
The following one-to-many relationships were created:
Date[Date]→Sales[Order_Date]Products[Product_ID]→Sales[Product_ID]Customers[Customer_ID]→Sales[Customer_ID]Salespersons[Salesperson_ID]→Sales[Salesperson_ID]Regions[Region_ID]→Sales[Region_ID]
This model allows the dashboard visuals and slicers to interact dynamically across different dimensions.
The dashboard uses DAX measures to calculate the main business KPIs:
| Measure | Purpose |
|---|---|
| Total Sales | Calculates total sales after discounts |
| Total Cost | Calculates total product cost |
| Total Profit | Calculates sales minus total cost |
| Profit Margin | Calculates profit as a percentage of sales |
| Total Units | Calculates total quantity sold |
| Total Orders | Counts unique orders |
| Average Order Value | Calculates average revenue per order |
| Previous Year Sales | Calculates sales for the previous year |
| YoY Growth % | Measures year-over-year sales growth |
| YTD Sales | Calculates year-to-date sales |
| Previous Year Profit | Calculates previous-year profit |
| Profit Growth % | Measures year-over-year profit growth |
The interactive dashboard includes:
- Total Sales
- Total Profit
- Profit Margin
- Total Orders
- Year
- Region
- Customer Segment
- Product Category
- Monthly Sales Trend
- Sales by Region
- Sales by Category
- Top 10 Products by Sales
All visuals respond dynamically to the selected filters, allowing users to explore sales performance from different perspectives.
The dashboard provides a high-level view of the company's sales performance and profitability.
Key areas of analysis include:
- Monitoring overall sales and profitability
- Comparing sales performance across regions
- Identifying the strongest product categories
- Identifying the top-performing products by sales
- Tracking monthly sales trends
- Evaluating profit margin alongside revenue
- Comparing current performance with the previous year
- Analyzing performance using interactive filters
Based on the dashboard analysis, businesses can use these insights to:
- Focus on high-performing products and categories
- Investigate regions with comparatively lower sales performance
- Monitor monthly sales trends to identify seasonal patterns
- Track profit margin alongside sales to avoid focusing only on revenue
- Use customer segment performance to improve targeting
- Review year-over-year growth to evaluate business progress
- Data Cleaning & Transformation
- Data Modeling
- Star Schema Design
- DAX
- Time Intelligence
- KPI Development
- Interactive Dashboard Design
- Data Visualization
- Business Performance Analysis
Completed ✅
The Power BI dashboard, data model, DAX measures, interactive filters, visualizations, and GitHub documentation have been completed.