Dave-s-Portfolio
# Motorcycle Sales Analysis (SQL)
📌 Context
This project analyzes motorcycle sales data to calculate net revenue and uncover trends in product performance and profitability.
🛠️ Techniques Used
- SQL: Data cleaning, filtering, aggregation
- Visual storytelling: Screenshots of key queries with annotations
📊 Process
- Data Cleaning
- Removed duplicate transaction IDs
- Standardized product category names
- Filtering
- Focused on transactions within the last 6 months
- Segmented by product category and store location
- Aggregation
- Calculated net revenue per product
- Grouped results to identify top performers
📷 Script Screenshots
Below are key SQL queries used in this project:
Net revenue calculation: Computing net revenue by product and grouping for analysis
📈 Results
- Top Products: Identified motorcycles generating highest net revenue
- Revenue Drivers: Calculated profitability metrics for inventory decisions
- Performance Insight: Grouped data revealed seasonal trends and top-performing models
🎯 Teaching Takeaway
This case study shows how calculating net revenue and grouping sales data can reveal actionable insights for inventory planning and product strategy.
🔗 Links
- SQL Script:
grocery_sales_analysis.sql