This is a Data Package with a sample of data provided by the Swiss startup Prognolite for the Open Food Hackdays 2018. This is a translation of the description contributed by one of the founders:

Prognolite solves one of the biggest problems of the restaurants - the unknown guests in the future. This problem leads to large inefficiencies in personnel planning and food purchasing, which causes a lot of food waste and high personnel costs. In addition, this can cause long waiting times, which does not happen if the number of guests were known in advance. With data on the cash register system and other data such as weather data and holidays, we can predict the number of guests / items sold in the future. Of course you can do other interesting things with the data.

PREVIEW (data.okfn.org)

About 300 MB of transactional data available from Juckerhof und Bächlihof will be available for the Hackdays. Every coffee or other sold is recorded within a one year period. In the data folder, you will find a small sample of this dataset.

Please contact us through the preparatory workshop if you have any questions, or talk to the challenge lead or organizers at the Hackdays.

The licensing terms of this data have not yet been established. If you intended to use these data in a public or commercial product, check with each of the data sources for any specific restrictions.

This README and other metadata contained in this Data Package is licensed by its maintainers under the Public Domain Dedication and License.