CSV files often arrive with duplicate records, inconsistent column names, blank required fields, mixed date formats, email whitespace, and encoding issues. A dependable cleanup workflow is: preserve the original; standardize headers; trim and normalize values; parse dates to ISO-8601; validate required fields; deduplicate using stable business keys; then export both a clean CSV and JSON for downstream systems.
For repeatable work, record each transformation and keep rejected rows in a separate file so nothing silently disappears. For a small dataset that needs a human cleanup rather than a script, I offer a flat $29 service with a 24-hour turnaround: cleaned/deduplicated CSV plus normalized JSON. Buy here: https://buy.stripe.com/3cI28t7YxgmGaRj7zRaR20u . After checkout, send a secure download link and requirements to vntrstds@gmail.com.
This is an optional paid service; the workflow above is usable independently.
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