Inducing a more data-driven decision making in a café environment.
Cafés are typically small businesses, most café owners, own only a few cafés with little knowledge and resources for inducing data-driven decisions. This project would help a particular café extract it’s data from various systems and collect it in a dashboard to easily investigate when making key changes in the business. The main goal of which is to help the café get a better overview of their operation while also providing future insights through forecasting that help them make critical decisions looking forward.
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Data from the café
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Potential interviews or other qualitative input
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Review data from various websites
Cloud_cover - (0-100%)
Humidity - (0-100%)
Precip_dur_past1h - (0-60 min)
Precip_past1h - (precip in mm)
Pressure - (some missing data / different methods of measurements)
Temp_dew - (degrees c - suppose it is a measure of humidity, but not sure)
Temp_dry - (degrees c - “air temperature”- some way of disregarding humidity’s effect on the temperature(?))
Temp_max_past1h - (degrees c)
Temp_mean_past1h - (degrees c)
Temp_min_past1h - (degrees c)
Wind_dir - (in degrees (0-360) - maybe transform to categorical variable)
Wind_max_per10min_past1h - (m/s)
Wind_speed - (m/s)
Wind_speed_past1h - (m/s)
Weather (no idea to be honest, values go from 100-185)
Temp_max_past_12h (degrees c, measured at 6:00 and 18:00)
Temp_min_past 12h (degrees c, measured at 6:00 and 18:00)
Wind_min_past1h (m/s)
Timon Florian Godt, Morten Hamburger, Daniel Bolander, Piratheban Rajasekaran