Project Description: Engineered an end-to-end Retail Data Analytics pipeline to process and aggregate thousands of raw transaction logs. Conducted rigorous Exploratory Data Analysis (EDA) and data cleansing operations utilizing Pandas to manage null values via median imputation and isolate duplicate/negative return records. Seamlessly integrated DuckDB directly over Pandas DataFrames to perform ultra-fast, in-memory SQL execution. Wrote complex SQL queries evaluating specific mathematical matrices like SUM(Quantity * UnitPrice) mapping GROUP BY City & Category logic variables. Generated actionable business intelligence resulting in a high-resolution Matplotlib Regional Sales bar-chart highlighting maximum revenue-generating hotspots.