Airbnb analysis

In this project, I worked with my team to perform a full data analysis cycle on Airbnb dataset.

Our workflow included:

Data Collection: Obtained raw Airbnb dataset covering listings, reviews, pricing, availability, and neighborhoods.

Data Cleaning:

Handled missing values and duplicates.

Standardized columns (dates, currencies, text fields).

Removed irrelevant and inconsistent records to ensure data accuracy.

Data Analysis & Processing:

Explored key metrics such as revenue, number of listings, cancellation policies, and customer preferences.

Segmented data by neighborhood, room type, and availability for deeper insights.

Visualization & Insights:

Built interactive dashboards in Power BI to highlight trends.

Identified top-performing neighborhoods (e.g., Bedford-Stuyvesant, Williamsburg).

Showed that entire homes/apartments generate the highest revenue, while flexible cancellation policies are more attractive to guests.

Compared availability across property types (hotel rooms vs. private homes).