Analyzed 1M+ sales transactions across 75 global stores over 4 years to evaluate product performance, geographic distribution, and warranty reliability. Created a dimensional model in DuckDB, resolved formatting inconsistencies, and queried data to uncover insights like an 872% variance in volume between top and bottom performing countries. Highlighted tight margins in warranty claims across categories, confirming broad product reliability and identifying stable non-seasonal sales floors.
A comprehensive exploratory data analysis of 1,020 employee records, taking it from messy raw data to actionable business intelligence. Cleaned missing values using grouped median imputation, analyzed salary distributions across departments, and uncovered a critical compensation misalignment: top performers earning as low as $50K while poor performers earn up to $119K. Built visualizations highlighting retention risks, regional salary patterns, and the impact of remote work on performance.
Brazilian E-Commerce Analytics ReportSQL · Python · Power BI
Deep-dived into 99,441 orders from Olist, a Brazilian marketplace, to uncover revenue drivers, customer behavior, and operational performance. Analyzed over R$ 13M in total revenue across 27 states, unearthing São Paulo's dominance at R$ 5.2M, severe logistic bottlenecks in the North with delivery times nearing 30 days, and a widespread dependency on credit card installments averaging 2.85 per transaction. Identified top-performing product categories, evaluated seller concentration risks, and mapped order status distributions revealing a 97% delivery success rate.
