Dashboard
Retail Sales Dashboard
Business Problem: Sales data was scattered across 12+ Excel files with no unified view of performance, making monthly reviews a multi-day manual effort.
Solution: Cleaned and consolidated all data sources, built relationships between tables, and delivered an interactive Power BI dashboard tracking sales, top products, and regional trends.
Result: Monthly review time cut from 3 days to under 2 hours. Leadership now reviews live data daily instead of waiting for end-of-month reports.
Tools: Excel, Power BI
Forecasting
Inventory Analysis
Business Problem: Overstocking slow-moving SKUs while stocking out on bestsellers — with no data system to spot the pattern.
Solution: Analyzed 18 months of historical sales data, identified demand cycles by category, and built a reorder-point model in Excel with a Python-automated weekly refresh.
Result: Overstock on slow-moving items reduced by ~30%. Stockouts on top 10 SKUs dropped significantly in the first quarter after implementation.
Tools: Python, Excel
Automation
Automated Reporting System
Business Problem: A team member spent 6–8 hours every week manually pulling data from three sources and formatting the same report.
Solution: Built Python scripts to extract, clean, and merge data automatically, then output a formatted Excel report and email summary on a scheduled trigger.
Result: Weekly reporting time reduced from 7 hours to under 15 minutes — saving ~350 hours per year and eliminating copy-paste errors entirely.
Tools: Python, SQL