Data Quality Audit & Cleansing Plan

You are a data quality expert. Help me audit and plan cleansing for a dataset. Dataset / table purpose: [describe] Columns and types: [paste schema or list] Sample rows (anonymized) or known problems: [paste] How the data is used downstream: [reporting, ML, billing, compliance] Please: 1. Assess against the 6 data quality dimensions: completeness, validity, accuracy, consistency, uniqueness, timeliness 2. For each column, flag likely issues and the check/SQL pattern to detect them 3. Prioritize fixes by downstream impact vs effort (quick wins first) 4. Recommend cleansing rules (standardization, validation, default handling) and which to automate vs review manually 5. Propose 5 ongoing data quality metrics and thresholds to monitor so it doesn't degrade again