This repository contains a Tableau dashboard for exploring hotel booking trends based on a dataset of hotel reservations. The dashboard allows users to conduct exploratory data analysis (EDA) to derive valuable insights into various factors affecting hotel bookings.
The dataset includes reservations from both city hotels and resort hotels, with features such as:
- Hotel type (City or Resort)
- Cancellation status
- Lead time
- Arrival date details
- Guest demographics
- Booking details (e.g., meal, market segment)
- Room details
- Deposit type
- Agent and company IDs
- Special requests
- Reservation status
The dataset comprises 119,390 rows and 32 columns.
To utilize the dashboard:
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Clone Repository or Download Dashboard File:
- Clone this repository to your local machine.
- Alternatively, download the Tableau dashboard file from the repository.
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Open Dashboard File:
- Open the dashboard file using Tableau Desktop or Tableau Online.
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Connect Dashboard to Dataset:
- Connect the dashboard to the provided dataset available in the repository.
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Explore Insights:
- Explore different pages and visuals within the dashboard to gain insights into hotel booking trends.
The primary goal of this dashboard is to conduct EDA on the provided dataset and derive valuable conclusions about broad hotel booking trends. The dashboard facilitates answering various questions related to factors influencing hotel bookings.
The dataset underwent several preprocessing steps, including:
- Removing duplicate values
- Handling null/missing values
- Removing outliers
- Converting columns to appropriate data types
- Creating new columns for additional insights
EDA was performed to answer key questions such as:
- Reasons for booking cancellations
- Impact of lead time on cancellations
- Distribution of reservation demographics
- Hotel type with the most advanced reservations
- Distribution channels with the highest cancellation rates
- Analysis of market segments
- Relationship between room type and Average Daily Rate (ADR)
- Busiest hotel types and months
- Revenue analysis based on hotel and customer types
- Parking space requests and other preferences
- Effect of waiting period on cancellations
- And more...
Various visualization techniques, including count plots, bar plots, line plots, box plots, and heatmaps, were employed for comprehensive analysis.
Key conclusions drawn from the analysis include:
- Preference for city hotels over resorts
- Impact of lead time on cancellations
- Distribution of reservations by demographics and preferences
- Revenue analysis based on hotel types and customer preferences
Challenges encountered during the analysis included:
- Handling duplicates and null values
- Formatting data types appropriately
- Selecting suitable visualization techniques
Tableau Dashboard Link - Hotel Booking Analysis
For more detailed insights, please explore the Tableau dashboard provided in this repository.