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
Tools: QGIS
Sources: Canterbury Regional Council • OpenStreetMap
Brief description:
A comprehensive cartographic analysis illustrating infrastructure networks across the Canterbury region. The map details arterial roads, state highways, and recovery plan areas, paired with a locator map to highlight the regional study area within New Zealand.
Key Findings:
Key Infrastructure Network: Mapped key regional transport corridors, including state highways (SH1, SH3, SH73, SH74, SH76) and arterial road networks across Canterbury.
Recovery Plan Integration: Visualized designated recovery plan areas to highlight spatial planning focus zones within the region.
Regional Contextualization: Incorporated an inset overview locator map to accurately frame the study area within the broader context of the South Island, New Zealand.
🔜 Currently in development — publishing soon...
Tools: Google BigQuery SQL • Tableau • Excel