Project Description
The tourism and hotel industry is a dynamic sector that contributes significantly to economic growth. In this project, we will evaluate hotel performance, customer satisfaction and booking trends by analyzing various reservation, hotel information, customer information and feedback data. Our aim is to optimize hotel management strategies, increase customer satisfaction and improve service quality. This analysis will help hotel managers and tourism industry professionals improve business processes and make strategic decisions.
Project Usage Areas
This project has several uses for hotel managers, tourism industry professionals and data analysts:
Analysis of Hotel Performance: Improving hotel performance by analyzing hotel occupancy rates, room prices and customer reviews.
Reservation Trends: Determining seasonal trends and customer preferences by analyzing reservation dates and stay durations.
Customer Satisfaction: Identifying ways to increase customer satisfaction by analyzing customer feedback.
Improving Service Quality: Using customer feedback to evaluate and improve hotel service quality.
Strategic Decisions: Developing hotel management and tourism strategies and optimizing business processes using data analysis.
Dataset Description
The data set to be used in this project includes tourism and hotel management data. The dataset consists of four main files in total:
Reservations
ReservationID: Reservation ID
HotelID: Hotel ID
CustomerID: Customer ID
ReservationDate: Reservation date
CheckInDate: Check-in date
CheckOutDate: Checkout date
RoomType: Room type (Single, Double, Suite)
Price: Price
Status: Status (Confirmed, Cancelled, Checked In, No Show)
Hotel Information (hotels)
HotelID: Hotel ID
HotelName: Hotel name
Location: Location (City Center, Suburb, Rural)
NumberOfRooms: Number of rooms
Rating: Evaluation (between 1-5)
Customer Information (customers)
CustomerID: Customer ID
CustomerName: Customer name
Gender: Gender
Country: Country
JoinDate: Join date
Feedbacks
FeedbackID: Feedback ID
CustomerID: Customer ID
HotelID: Hotel ID
FeedbackDate: Feedback date
Rating: Evaluation (between 1-5)
Comments: Comments
There are various dirty data problems in this dataset, such as missing data, outlier data, and wrong data type. This is an ideal data set to experience data cleaning and processing processes commonly encountered in real life.
Student Benefits
This project provides many benefits for students:
Data Manipulation: Students develop skills in examining, cleaning, and analyzing data sets.
Using Pandas: They learn to use the data processing and analysis methods of the Pandas library effectively.
Data Cleaning: They gain skills in cleaning missing data, outliers and incorrect data types.
Business Intelligence: By analyzing data sets, they improve their ability to evaluate hotel performance and customer satisfaction and make strategic decisions.
Reporting: Provides skills to effectively report and present analysis results.
Real Life Applications: Provides practical information about data problems and analysis processes encountered in real life.
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