inventory-analytics

Built an interactive Excel-based inventory dashboard using PivotTables, charts, slicers, and conditional formatting to monitor stock levels, reorder status, and supplier-wise performance across warehouses. Enabled 30% faster analysis and reporting through real-time, data-driven visualizations for supply chain decisions.

AI-powered Retail Intelligence & Demand Forecasting Platform. Predicts 30-day unit sales velocity, stockout risks, and capital-locked inventory using XGBoost & Machine Learning.

End-to-end E-Commerce Sales, Inventory & Business Analytics platform using Python, Pandas, SQL, MySQL, Pytest, Matplotlib & GitHub Actions.

Supply Chain & Inventory Analytics — pipeline end-to-end (40 SKUs, 5 WH, 8 suppliers): turnover, DIO, stockout, lead time & Inventory Health Score. Streamlit + Plotly. No ML.

Inventory management and dead stock risk prediction system using Python, MariaDB, Pandas, Matplotlib, and Tkinter.

Standalone, runnable reconstruction of a production inventory-intelligence pipeline — demand classification, IQR outlier cleaning, inventory turnover & aging-stock analytics — on synthetic data. Python · DuckDB · pandas · Streamlit.

Pharmacy inventory analytics portfolio covering stock value, expiry risk, dead stock, slow-moving items, reorder candidates, SQL analysis, and an interactive dashboard.

Retail inventory analytics · Python → PostgreSQL · 3,732 Zepto SKUs · 14 SQL queries · stock health & revenue insights

Visualizing retail revenue, customer segmentation, and seasonal trends through SQL-driven analysis and Tableau.

Senior/Lead Power BI control-tower case study for inventory decisions, governed metrics, reliability, and operating model.