DataDoctor

Runs entirely in your browser — no uploads, no saved snippets, no public links.

Paste a file, inspect the issues, export reviewed output.

CSV dedupe preflight

CSV Duplicate Finder

Find duplicate rows by one or more key columns, with options for case and whitespace normalization.

Paste CSV, load the customer sample, or upload a local file.

Next workflow

Continue the preflight

CSV Cleaner

Remove duplicates or incomplete rows after review.

CSV Data Quality Checker

Profile broader CSV quality risks.

CSV Validator

Check parse errors before dedupe.

After the tool runs

CSV Duplicate Finder review guide

Use the tool above first. The supporting notes below help you interpret the result, fix the right issues in the right order, and choose the next DataDoctor tool without pushing SEO content above the actual task.

Best input

finding duplicate CSV rows or duplicate business keys before removing anything.

Output to keep

Save the original file, the issue report and the reviewed export as separate files.

Next check

After structural and quality issues are visible, run a platform checker or schema validator before upload.

What it checks

CSV Duplicate Finder for real data work

CSV Duplicate Finder should sit before the import screen, not after a failed upload. It turns hidden spreadsheet problems into a checklist you can review row by row.

  • Selected duplicate key columns
  • Case-insensitive matches
  • Whitespace-insensitive matches
  • Duplicate and deduplicated exports

Fix these first

Common errors to review before downstream work

Most failures come from small file issues that become expensive only after an API call, import job or spreadsheet cleanup. Fix blocking errors first, then re-run the same tool before moving forward.

  • Using the wrong duplicate key
  • Email case differences
  • Whitespace around IDs
  • Removing rows without saving a duplicate-only file

Recommended workflow

Run the check in this order

Treat any downloaded output as a reviewed candidate. Keep the source CSV unchanged so you can reconcile removed rows, duplicate groups or missing values later.

  1. Step 1

    Paste the CSV

  2. Step 2

    Choose key columns

  3. Step 3

    Run duplicate detection

  4. Step 4

    Download duplicates or a deduplicated file for review

How to interpret a passing result

A pass means this specific preflight did not find the issues listed above. It is not a guarantee that the target system will accept every row, field, custom mapping or account-specific rule.

Do not clean, deduplicate or drop rows before parser errors, required columns and duplicate-key logic are clear.