{"id":19704057,"url":"https://github.com/mayankyadav23/air-bnb-data-analysis","last_synced_at":"2026-03-19T11:10:17.497Z","repository":{"id":257420451,"uuid":"858215346","full_name":"mayankyadav23/Air-BNB-Data-Analysis","owner":"mayankyadav23","description":"Data analysis and insights from NYC Airbnb listings, focusing on key metrics such as host performance, neighborhood trends, pricing, and customer reviews. Comprehensive documentation of ETL processes and analytical methodologies is provided. 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This analysis seeks to derive meaningful insights from historical booking data of homestay listings in New York City. To do so, we will employ the Extract-Transform-Load (ETL) process to analyze key aspects of the data, answering essential research questions related to:\n\nHost Engagement \u0026 Performance\nNeighborhood Popularity \u0026 Trends\nCustomer Pricing Strategies\nGuest Reviews \u0026 Satisfaction\nBy exploring these factors, this report aims to uncover patterns and insights that can help enhance Airbnb's travel offerings and improve both host and guest experiences in NYC.\n\n# 🛠 Tools Used\n\n1. Excel\n2. Power BI\n3. Power Query\n4. PowerPoint\n   \n# 📉 Dashboard\n\n![image](https://github.com/user-attachments/assets/81876088-7d46-41be-b1e3-0876c641fe35)\n\n\n![image](https://github.com/user-attachments/assets/25b1e305-2ec4-48d9-b697-edc6273e13e3)\n\n\nWatch the complete Dashboard video [Link](https://www.youtube.com/watch?v=KEbqDzawWGA)\n\n# ✔️ Key Insights from NYC Airbnb Homestay Analysis\n\nOur comprehensive analysis of Airbnb homestays in New York City reveals intriguing trends and preferences in customer behavior, host success, and pricing strategies. Below are the standout findings:\n\nManhattan: The Epicenter of Airbnb Activity\nManhattan dominates the Airbnb market with the highest number of bookings across all neighborhood groups. Notably, the top-earning hosts also have the majority of their bookings in this area, solidifying Manhattan as the most preferred destination for travelers.\n\nPricing Paradox: High Prices, Fewer Bookings\nInterestingly, neighborhoods with the highest average pricing tend to experience fewer bookings. This suggests that while premium areas exist, they are less frequently chosen by guests.\n\nPrice vs. Reviews: Consistent Across the Board\nWhen comparing average pricing with review scores, the pricing remains relatively consistent across various review ratings, indicating minimal correlation between price and customer review scores (out of 5).\n\nRoom Type Preferences\nTravelers overwhelmingly prefer Entire Homes/Apartments and Private Rooms as their accommodation types. Despite being the most popular, these room types also boast lower average pricing compared to other options.\n\nManhattan’s Room Type Breakdown\nWithin Manhattan, 88% of the bookings are for Entire Homes/Apartments, reinforcing its appeal as a destination for guests seeking privacy and a complete space to themselves.\n\nThese insights offer a clear understanding of the current trends in the New York City Airbnb market, helping hosts and travelers make more informed decisions.\n\n# 🗂 Documentation\n\nHigh Level Design Document [Link](https://github.com/user-attachments/files/17014813/HLD.BusinessAnalyst.iN.pdf)\n\nLow Level Design Document [Link](https://github.com/user-attachments/files/17014819/LLD.BA.iN.pdf)\n\n\nArchitecture [Link](https://github.com/user-attachments/files/17014831/BA.Architecture.iN.pdf)\n\nWireFrame  [Link](https://github.com/user-attachments/files/17014837/BA.Wireframe.iN.pdf)\n\n\nReport [Link](https://github.com/user-attachments/files/17014898/Air-BNB.Data.Analysis.Report.pptx)\n\n\n# 📩 Feedback\n\nIf you have any feedback, please reach out to me at [Linkedin](https://www.linkedin.com/in/mayankyadv?utm_source=share\u0026utm_campaign=share_via\u0026utm_content=profile\u0026utm_medium=android_app)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmayankyadav23%2Fair-bnb-data-analysis","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fmayankyadav23%2Fair-bnb-data-analysis","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmayankyadav23%2Fair-bnb-data-analysis/lists"}