Survey Data Cleaning (Portfolio Project)
Bennett completed survey data cleaning by removing errors and standardizing datasets for reliable analysis. The effort improves data quality so the resulting dataset can be used for annotation or modeling tasks. This experience emphasizes preprocessing steps that are commonly required before labeling. • Removed errors from survey records • Standardized fields and formatting across the dataset • Organized the cleaned dataset for further processing • Prepared structured data suitable for future labeling/ML use