Data Processingdaemon-blockint-tech/agen...
data-scrubbing
Guides cleaning and standardizing tabular datasets before analysis, modeling, or reporting—profiling,
quality rules, missing values, duplicates, outliers, type coercion, encoding fixes, record linkage,
deduplication, high-level PII handling (not legal advice), actuarial/insurance field scrubbing,
reproducible scrub pipelines, validation checks, and sign-off. Distinct from warehouse ETL or
statistical modeling. Use when the user asks for "data scrubbing", "clean this dataset", "scrub the
data", "data cleaning", "dedupe records", "handle missing values", "outlier treatment",
"standardize columns", "data quality rules", "profile this table", or "prepare data for modeling".
Not warehouse pipelines (data-warehouse-engineer), ML modeling (data-scientist, actuary), privacy
programs (compliance-engineer), FinOps only (finops-analyst), or assumption governance
(assumption-setting).