PRACTICAL WORKFLOWS
CSV import checklist: validate a file before uploading it
Check headers, identifiers, missing values and a small sample before importing a CSV.
Start with the destination fields
Read the import screen's field requirements before editing a file. List required columns, accepted date formats and the identifier used to update an existing record. Keep a copy of the original export so you can trace any changes.
Check the shape and meaning
- There is one header row and every column has a distinct name.
- Each row has the expected number of fields.
- Required identifiers are present and have the intended uniqueness.
- Phone numbers and account codes retain meaningful leading zeros.
- Empty values are distinguishable from zero and from the word “unknown.”
- Dates use one documented format and include a time zone where needed.
Map explicitly
Write down how each source field maps to the destination. Do not guess that “name” means a company name when it contains a person's name. Preserve source IDs if the destination can store them.
Source column | Destination field | Transformation company | organization | trim surrounding spaces source_id | external_id | preserve as text collected_at | source_checked_at | verify date format
Import a small sample
Use a test area or the destination's preview when available. Include a row with non-English text, a missing optional field and a value containing a comma. Confirm that updates and new records behave as expected before uploading the full file.
Reconcile the result
Compare submitted, accepted and rejected row counts. Save the rejection report and investigate failures rather than repeatedly importing the same file. The CSV cleaner can help remove exact duplicate rows and whitespace before this review.