📌 Project Overview
This project analyzes Airbnb listings and reviews using Power BI to uncover insights about pricing, availability, neighborhood trends, and customer engagement. The dashboard is designed to be interactive, enabling exploration across multiple dimensions such as neighborhood, room type, and price category.
🗂️ Dataset Details
The project is based on three Airbnb datasets:
listings.csv → Host details, price, room type, availability, and location data.
reviews.csv → Guest reviews with ratings and feedback count.
neighbourhoods.csv → Mapping of listings to neighborhood groups.
Total records analyzed:
111K listings
7,842 hosts
505K reviews
📊 Dashboard Features
Key Metrics at a Glance → Total Hosts, Listings, Average Price, Total Reviews, Current Availability.
Neighborhood Analysis → Distribution of listings, hosts, and reviews across top areas.
Room Type Breakdown → Entire home, private room, shared space, hotel room.
Price Segmentation → Low, Medium, High categories with availability and frequency.
Interactive Filters → Slicers for Neighborhood, Room Type, and Price Category.
Time-Based Trends → Monthly and yearly review activity visualized with maps and charts.
🔍 Key Insights
87% of hosts offer entire homes, indicating strong demand for full-property rentals.
The Central Business District dominates with over 45K listings, showing high competition.
Low-price categories have the highest availability, revealing a market driven by budget-friendly stays.
Seasonal review spikes highlight periods of higher tourism demand.
🛠️ Tools Used
Power BI → Dashboard design and data visualization
DAX → Custom measures for Price Category and KPIs
CSV Datasets → Listings, Reviews, and Neighborhood data
📷 Dashboard Preview
