A data analytics project focused on cleaning, analysing, and visualising retail sales data using Excel, SQL, and Power BI.
This project analyses retail sales data to uncover insights into revenue, profit, customers, and product categories. The workflow includes data cleaning, SQL-based analysis, and dashboard creation for effective business decision-making.
✅ Data cleaning and preprocessing in Excel ✅ SQL queries for business analysis ✅ Customer and category performance analysis ✅ Revenue and profit calculations ✅ Interactive Power BI dashboard ✅ Data-driven business insights
- 📊 Microsoft Excel – Data cleaning and preparation
- 🗄️ SQL – Data analysis and querying
- 🛠️ MySQL Workbench – Database management and query execution
- 📈 Power BI – Dashboard creation and visualization
- Removed null and empty values
- Fixed date formatting issues
- Eliminated unnecessary spaces
- Prepared dataset for analysis
- Total Revenue Analysis
- Total Profit Analysis
- Top Customers by Sales
- Top Categories by Sales
- Top Categories by Profit
- Sales Dashboard
- Revenue Trends
- Profit Analysis
- Customer Insights
- Category Performance
- Data Cleaning Techniques
- SQL Query Writing
- Business Data Analysis
- Dashboard Design
- Data Visualization Best Practices
- Advanced KPI Tracking
- Sales Forecasting
- Customer Segmentation
- Time-Series Analysis
- Interactive Drill-Through Reports
Afreaz
🎓 BCA Graduate 📊 Aspiring Data Analyst 🐍 Learning Python, SQL, Excel, and Power BI
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