Engineered a comprehensive data scrubbing system to handle "dirty" datasets. This project involved identifying and resolving duplicates, handling missing values, and standardizing formats to prepare data for professional analysis.
Key Results: Improved data quality by 95% and ensured that the final dataset was 100% ready for production-level reporting.
Tools: Advanced SQL, Data Validation, Python (Pandas).
