SQL | Python | Tableau | Data Visualization
End-to-end supply chain analytics project using SQL, Python, and Tableau.
- SQL
- Python (Pandas)
- Tableau
• Revenue by Warehouse
• Order Volume Trend
• Shipping Delay Rate
• Inventory Levels
• Revenue by Category
Key operational insights from the dashboard:
• The Texas warehouse generates the highest revenue, indicating it is the primary fulfillment hub.
• Electronics account for the majority of total revenue compared to furniture.
• The shipping delay rate is relatively low, with most orders delivered on time.
• Inventory levels show uneven distribution across products, suggesting potential overstock or demand imbalance.
• Order volume fluctuates over time, indicating demand variability that could impact supply planning.
- SQL queries analyze warehouse and order data
- Python performs exploratory analysis using Pandas
- Tableau visualizes operational KPIs
- Texas warehouse generated the highest revenue
- Electronics category dominates total revenue
- Most deliveries are on time with a small delay percentage
- Inventory levels vary significantly across products