Tools: Google BigQuery SQL • Tableau • Excel
Brief description:
An end-to-end retail data analysis of 1,000 supermarket transactions across three branches. Using Google BigQuery SQL for data validation and exploratory analysis, I uncovered hidden revenue opportunities, peak hour staffing gaps, and pricing inefficiencies across all product lines.
Key Findings:
• $58,202 in uncaptured E-wallet loyalty revenue identified
• Peak trading at 7PM — 113 transactions — staffing gaps uncovered
• Flat 4.76% margin across all product lines — pricing inefficiency found
• Food & Beverages led revenue at $56,145 across 174 orders
🔜 Currently in development — publishing soon...
Tools: Google BigQuery SQL • Tableau • Excel
🔜 Currently in development — publishing soon...
Tools: Google BigQuery SQL • Tableau • Excel