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Data-subject workflow

Remove a Person’s Records from a CSV Dataset

Locate all records linked to a data subject, review dependencies and produce evidence of a controlled removal.

Use the matching tool

GDPR Data Removal

Open GDPR Data Removal

What the error actually means

A person may appear under several identifiers and across related exports. Deleting one exact-name row may leave email, phone, account or transaction-linked records behind. The applicable legal basis, retention duty and scope require organizational review.

Likely causes

  • Several identifiers refer to the same person.
  • Names have spelling variants.
  • Related records use internal IDs.
  • Some records must be retained under another obligation.

Identifier set

Problem

Delete only rows where name equals Ada

Correct pattern

Use verified subject identifiers and review linked records under the approved scope

A safe repair workflow

  1. 1Verify the request and approved scope.
  2. 2Assemble the subject’s authorized identifiers.
  3. 3Find candidate rows and review dependencies.
  4. 4Remove approved records from a copy and document counts.

How to verify the result

A file that downloads successfully is not automatically a correct file. Check the result at both the structural and business-data levels:

  • Every authorized identifier was checked.
  • Linked records were considered.
  • Exceptions have a documented basis.
  • The result and audit evidence are stored appropriately.

Read the deeper guides

How to Anonymize CSV Data Without Ruining the DatasetA practical method for removing or replacing names, emails, IDs, dates, and other identifying fields while preserving useful CSV data.How to Clean CSV Data Without Hiding the Original ProblemsLearn practical techniques to clean messy CSV files. Remove duplicates, fix formatting, and standardize data without Excel crashes or complex scripts.