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.
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.
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.
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