Data Mining in Chain Hotels Assignment Example | Topics and Well Written Essays - 1750 words

Data Mining in Chain Hotels - Assignment Example Databases can be used by several users seeking businesses in this sector. It helps them to overcome challenges of competition and meet the demands of the market. Â  This study seeks to develop a database for hotel chain management operating 20 hotels in 4 countries. The data mining for the store of information for each hotel and performs analysis with regard to the given hotel. For each hotel the data warehouse will store its name, type, address, country, region, postcode, phone number, and the name of the manager. The data also include different types of rooms like single, double, family, suits, etc. Each room may also incorporate certain optional features, such as refrigerator, kitchenette, or laundry. The system should have each room described as room’s type, size, number of beds, the maximum number of customers, refrigerator (Boolean), kitchenette (Boolean), laundry (Boolean). The capacity of the hotel chain to accommodate customers is limited. The database should help the management on how to price the hotel rooms in order to realize maximum revenue collection. Looking at the capacity of the hotel over time given in the data ware house, they can easily come up with the prices. Comparison between the occupancy rate (utilization) and the vacancy rate is considered. Â  The hotel chain’s capacity to accommodate customers is limited. Each hotel has a set number of rooms. The primary source of revenue is accommodation in hotel rooms. The biggest challenge the company faces is determining how to price the hotel rooms. If they are priced low, the hotels will be constantly booked and therefore customers will be forced to try other hotels in competition with The Grande Chat and if the rooms are priced too high, a lot of rooms will remain empty. The hotel chain management wants to realize profits. The only way is to use the data mining to realize their underlying, interesting patterns and relationships that lie hidden within the analysis (Data mining).