Data Scrubbing

When to Use

• Profile a table or file and define data-quality rules before analysis or modeling
• Clean, standardize, dedupe, or link records in CSV, Parquet, SQL extracts, or notebook pipelines
• Treat missing values, duplicates, outliers, types, encodings, and column naming consistently
• Document a reproducible scrub pipeline with validation checks and sign-off criteria
• Scrub actuarial/insurance fields (policy keys, claims triangles, exposure bases) for downstream reserving or pricing prep
• Flag or redact PII at a technical level before sharing extracts (coordinate with compliance for legal requirements)

When NOT to Use