A Simple Data Integrity Checklist Before Conversion

Format conversion is successful only when the meaning of the data survives.

Count records Compare the number of input and output records. A mismatch is an immediate signal that rows were skipped, merged or split.

Check required fields Choose a few fields that must never disappear—IDs, dates, amounts or names—and inspect them in several records after conversion.

Watch null and empty values An empty string, missing field and null value can have different meanings. CSV has no universal built-in null representation, so your workflow needs a convention.

Confirm types Leading zeros, long numbers, booleans and dates are common type traps. A spreadsheet may reinterpret values even when the converter produced them correctly.

Sample edge cases Test rows containing commas, quotes, new lines, non-English text and emoji. These are more likely to reveal encoding or escaping bugs than a simple clean sample.

Keep the source Do not overwrite the only copy during a conversion test. Save the output separately until you have validated structure and counts.