This project aims to optimize inventory management for a mid-sized retail company by identifying inefficiencies through advanced SQL-based analytics. Using realistic data and schema design, it delivers a powerful combination of queries, forecasting models, and dashboard insights.
To analyze inventory data using SQL and visualize inefficiencies such as:
- Overstocking and understocking
- Demand-supply mismatches
- Regional performance differences
- Reorder optimization
You can view the interactive Power BI dashboard using the following link:
| File/Folder | Description |
|---|---|
schema.sql |
SQL script to create the database schema (tables, relationships) |
data_filling.sql |
SQL script to populate the tables with mock transactional data |
query.sql |
SQL queries for key analytics insights (e.g., slow-moving products, reorder points, etc.) |
inventory_forecasting.csv |
Dataset provided |
Dashboard.pbix |
Power BI dashboard file showcasing key KPIs and analytics visuals |
Dashboard.pdf |
PDF version of the dashboard for quick reference |
ERDiagram.png |
Entity Relationship Diagram illustrating schema design |
presentation.pdf |
Final presentation outlining problem statement, solution methodology, and results |
sql_documentation.pdf |
Documentation of SQL logic and rationale behind query development |
README.md |
Project overview and documentation (this file) |