You find duplicate customer records in a dataset. How do you handle them?

What the interviewer wants to hear

• Defines what counts as a duplicate (exact vs same entity)
• Measures how many duplicates exist and why
• Chooses a rule for which record to keep
• Deduplicates in a repeatable way such as ROW_NUMBER
• Reports the issue to the source owner

Model answer

First I decide what a duplicate means here. Exact copies of a row are easy, but the same customer may also appear with a different spelling or email case, so I check by a business key such as phone number or normalised email. Then I measure the size: how many rows are affected and whether they cluster around one source or date, which hints at the cause, like a double import. Next I agree a keep rule, for example keep the most recently updated record, and apply it in a repeatable way, such as ROW_NUMBER partitioned by the key and ordered by updated_at descending, keeping row 1. I never just delete rows by hand in a spreadsheet. Finally I note the change in my analysis and tell the data owner, so the problem is fixed at the source.

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