CSV Import Checklist for Silent Data Errors

A CSV file may open cleanly and still contain errors that appear only after import. Leading zeros can disappear, dates can change meaning, and a comma inside a company name can shift values into the wrong columns if parsing is incorrect. A useful checklist tests the file as data, the destination's interpretation, and the resulting records. Visual inspection of the first few rows is only one part of that review.

Freeze the input and define its shape

Keep an approved original and work on a versioned copy. Record the expected row count, column names, delimiter, encoding, and meaning of each field. Decide how blanks, unknown values, and intentional removals differ. An empty cell should not accidentally mean “erase the current value” unless that behavior is explicitly intended and supported.

RFC 4180 documents quoting for fields containing commas, line breaks, or double quotes. Use a proper CSV parser or exporter rather than splitting every line at each comma. Confirm the destination's accepted format because implementation details can differ.

Test values that are easy to misread

• Identifiers with leading zeros or more digits than a spreadsheet displays comfortably.

• Dates that could be interpreted in more than one regional order.

• Names containing accents, non-Latin characters, commas, or quotation marks.

• Long text fields with line breaks.

• Whitespace-only values and repeated header rows inside the file.

• Duplicate identifiers and references to accounts absent from the destination.

Choose the expected type for every column. Treat identifiers as labels rather than quantities. For dates, use an unambiguous representation accepted by the importer and verify a known example after import. Never repair uncertain dates by guessing which regional interpretation seems more likely.

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Check for formula interpretation

Untrusted spreadsheet values need a security review. OWASP documents CSV formula injection and warns that mitigation behavior can vary across applications. Do not open an unfamiliar export with active formula interpretation merely to inspect it. Use an approved safe review method and consult the responsible technical owner if the file contains suspicious values.

Do not rely on ordinary CSV quotation alone as a universal security fix. A file intended for human spreadsheet viewing may need different handling from a machine import. Preserve the source separately and document any sanitization so a protective change does not silently alter a business identifier or downstream meaning.

Fictional example: a shifted company row

In this fictional example, a file contains a company called Elm, Stone and Co. Its name was not quoted correctly, so an importer interprets the comma as a column boundary. The address moves into the wrong field, and later values shift. A check of header count against parsed field counts catches the malformed record before the file reaches the customer system.

The same pilot includes an identifier written as 00427. The reviewer verifies that the destination retains all five characters and that an ambiguous date is rejected for clarification. These are illustrative test cases, not evidence that a particular product has these defects.

Reconcile the destination, not just the file

Compare attempted rows with accepted, rejected, created, and updated records. Inspect several values from each relevant edge case and check relationships. A matching total can still hide wrong field mappings. Keep rejection reasons and decide which rows need correction, exclusion, or further evidence.

Use a reversible import pilot before a large change. If the list has broad quality problems, create a remediation plan rather than repeatedly editing the file until the importer stops complaining.

For the US$15/month offer, verify whether any file delivery is included and which formats are actually supported. Do not assume an export is import-ready or that its availability grants permission for every downstream use.

Finish with a signed-off mapping and a brief reconciliation record. That makes the next import repeatable and gives the team a concrete place to investigate if a silent error appears later.