Dataset: Hotel Booking Demand Dataset

The primary commodity (the hotel room) is perishable product within 24hrs and for everyday in the calendar it has a very different lead-time with its corresponding room rates.

Eg: For Room A on 25th August 2019 every hour before the booking time on 25th Aug is a lead time, which can have different pricing. (Const pricing vs Dynamic pricing)

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Also the pricing of the room is dependent on the number of rooms left on the booking date, pricing of competitors in the area, events in the area, seasonality, day of the week, month of the year, inbound flight and train patterns of the region, meteorological information of the region etc.

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I want to know if there are people who have already worked on a problem solution, similar to this in the hotel industry? If yes what are the techniques of Data framing that you used and the models that you have tried this on?