Analyzed transaction data from three NYC locations of Maven Roasters to uncover sales patterns and operational efficiencies. Tasks included revenue calculation, date/time extraction, PivotTable creation, and dashboard development. Recommendations were made to optimize operational hours and improve profitability for the Lower Manhattan branch.
E-ASTEKPAM: Sistem elektronik untuk laporan ASTEKPAM. Cepat, terstruktur, catat unit, tanggal, peralatan, arahan. Fasilitasi transisi keamanan.
This is my Stanford University Code in Place final project code. It is a visualization of some of part of the operations data. The code is written in python.
Data analysis of physician shift data for hospitals using Google Sheets, featuring data visualization, performance insights, and interactive filters
PubPilot: The Ultimate AI Companion for Bar Management Excellence
A series of simple-to-advanced analyses on energy usage (kWh) and operational costs for Austin Street Brewery, spearheaded by a collaboration with NEEFC.
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