Hotel Data Technical Report (Data Science)

We conducted a thorough analysis of the hotel bookings and cancellations dataset in order to generate insights that we believe will be beneficial to hotel management and the hospitality industry as a whole.

The insights gained from our data analysis indicate that a variety of factors contribute to cancellation rates; these conclusions were transformed into recommendations that we believe will positively impact booking rates, thereby lowering cancellation rates and increasing revenue.

We analyzed a dataset of over 40,000 bookings using twenty variables to develop models for visualizing the data and identifying patterns and trends that serve as significant indicators and eventually insights that can be converted into recommendations.

To arrive at these conclusions, a multi-step process began with loading the data and cleaning it, followed by analyzing each variable separately, and then by analyzing the variables in conjunction with the dependent and predictor variable 'IsCanceled' using box plots, bar graphs, and histograms.