Import CleanerImport Cleaner

CSV file validation: the checks to run before importing

5 min

A CSV import rarely fails because of the data itself: it fails because of the file structure. Validating the file before sending it to a third-party tool saves hours of rework.

The validation checklist

Six checks cover almost every rejected import.

  • Delimiter: comma, semicolon, tab or pipe. Automatic detection avoids opening a file as one single column.
  • Encoding: UTF-8 expected; otherwise accents and special characters are corrupted.
  • Schema consistency: every row must have the same column count as the header.
  • Quotes: one unclosed quote shifts the rest of the file.
  • Data types: no text in an amount column, no invalid date.
  • Uniqueness: the key (email, ID, SKU) must appear only once.

Separator and quote traps

A comment field containing an unescaped comma or semicolon shifts the columns of that row. The file still looks fine to the eye but becomes unusable for a strict parser.

Import Cleaner detects rows whose column count differs from the header, flags unclosed quotes and cleans stray line breaks inside cells.

Validate and fix in the same tool

A validator that only reports leaves all the work to you. Import Cleaner shows row-by-row traceability with the issue type and the suggested corrected value, then exports a compliant file.

You review the final sheet, corrected columns and rows, before downloading.

FAQ

What file size is supported?
Large files are processed in batches in the browser, with an alert when the classic Excel limits are exceeded.
Does the validator detect the delimiter automatically?
Yes, comma, semicolon, tab and pipe are recognised when the file opens.

Validate your CSV before importing

Structure, encoding, types and duplicates checked in one pass.

Check my file