Spare Parts

I built a Spare Parts Sales and Inventory Dashboard starting from the database itself.

I designed the SQL database using DDL and DML, created relationships between tables, and structured it using a star schema model.

After that I connected it to Power BI and developed an interactive dashboard for sales, purchases, customers, employees, and stock tracking.

Key findings:

• Total sales reached 4.15M while unpaid customer debt reached 1.62M → clear cash flow issue.

• More than half of the inventory is already reserved which increases stock-out risk.

• Sales peak in month 1 and month 10 and drop in month 4 and month 12 → seasonal demand pattern.

• A small group of employees generates most of the revenue → performance dependency risk.

Business actions that can be taken:

Improve credit policy and follow up on high-debt customers.

Set reorder points for fast-moving spare parts.

Run promotions during weak months.

Train the rest of the sales team using top performers’ methods.

This project shows how data can guide operational decisions instead of relying on assumptions.