This project focuses on analyzing financial revenue data to identify trends, profitability, and overall business performance. SQL is used for data processing, Excel for validation, and Power BI for building an interactive financial dashboard that supports data-driven decision-making.
- Analyze total revenue and profit
- Track monthly and yearly revenue trends
- Identify top-performing products and regions
- Compare revenue against profit margins
- Deliver an executive-level financial dashboard
- SQL (MySQL) – Data cleaning and analysis
- Microsoft Excel – Data validation and preprocessing
- Power BI – Data modeling and visualization
The dataset consists of structured financial transaction data with the following columns:
- Transaction_ID
- Date
- Product_Category
- Region
- Revenue
- Cost
- Profit
The structure aligns with standard financial reporting datasets.
- Removed duplicates and handled missing values
- Verified numerical accuracy for revenue, cost, and profit
- Standardized date formats
- Created a financial database
- Imported cleaned data into SQL tables
- Verified row counts and data integrity
Key analysis performed:
- Total revenue and total profit calculation
- Monthly and yearly revenue trends
- Product category-wise revenue
- Region-wise financial performance
- Profit margin analysis
- Connected Power BI to SQL database
- Built KPI cards for revenue, profit, and margin
- Created visualizations:
- Line chart for revenue trends
- Bar chart for category-wise revenue
- Regional performance charts
- Summary KPIs for executives
- Identified high-revenue and high-profit product categories
- Detected seasonal patterns in revenue
- Highlighted regions with strong and weak financial performance
- Revealed areas with low profit margins despite high revenue
- Interactive filters for date, region, and category
- Dynamic revenue and profit tracking
- Clear financial insights for business stakeholders
This project demonstrates an end-to-end financial revenue analysis workflow usi