CSV Cleanup and Audit Trail | Synthetic Demonstration

CSV Cleanup and Audit Trail | Synthetic Demonstration Self-directed workflow demonstration using fictitious data. The local Python workflow cleans agreed CSV fields while preserving source records and review decisions. It trims whitespace, normalizes the configured email field, combines only exact duplicates and flags uncertain or conflicting values for review. Verified sample results 12 source records; 11 retained records; 1 exact duplicate combined; 11 issue/review entries; 7 logged changes. All 12 original records remain traceable. Handoff Cleaned CSV, issue list, field-level change log, original-record ledger, summary, reusable Python source and run instructions. Boundaries Email checks assess syntax, not deliverability. Similar records are flagged and retained. The example uses a small synthetic dataset. A larger file, Excel-specific features or new columns require sample validation before a price or turnaround commitment. Tools: Python standard library, CSV and JSON, local processing.