
This project focuses on preparing the Airbnb Listings Dataset for structured analysis. The work includes data exploration, cleaning, handling missing values, and feature engineering to ensure the dataset is reliable for analytical or predictive tasks.

• Increased profitability by 34% in 2014, generating $251k in profit from a total revenue of $725.46k, achieving the highest profit year-to-date

Built a Bronze–Silver–Gold medallion pipeline in Microsoft Fabric using Python (Pandas, Spark) to clean and transform 9,000+ retail records, bringing data reliability up by 30%

• Utilized advanced Excel tools such as Pivot Tables, VLOOKUPs, custom formatting, and charts to effectively analyze and present Superstore sales data
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