Check charset and headers before a ServiceNow CSV import

Match the Import Set header before the data

ServiceNow's file data source documentation describes CSV imports around a header row, delimiter, and character set. A file can parse successfully and still map to the wrong target table if the header names or order are not the fields expected by the transform map.

• Garbled text: confirm the source charset, then convert to the charset selected in the data source.
• Fields shift: inspect commas, tabs, quotes, and the row with a different column count.
• Import Set fields are blank: compare the first row with the transform map, not only with a spreadsheet view.

• Diagnose CSV column counts and quoted fields →Review structural findings before changing a value or header.
• Check the CSV character encoding →Choose the source encoding from the preview instead of guessing from the country.
• Select the columns required by the template →Remove export-only fields while keeping all data rows.

Decide whether the defect is structural or semantic

Open a copy of the export as text and record the delimiter and encoding that actually produce the expected columns. Structural checks can be done locally; field mapping, coalesce behavior, and transform scripts remain ServiceNow decisions.

• Use the exact Import Set data source and transform map as the source of truth for headers.
• Do not treat a blank value as a missing column until quoted empty fields and trailing delimiters are checked.
• Keep an untouched source file so a failed transform can be reproduced.

• Diagnose CSV column counts and quoted fields →Review structural findings before changing a value or header.
• Check the CSV character encoding →Choose the source encoding from the preview instead of guessing from the country.

Diagnose and convert in two explicit steps

LocaCSV does not infer ServiceNow business fields or silently repair an unclosed quote. A diagnosis that stops is a signal to fix the source export deliberately.

1. 1Copy the source export and open it in LocaCSV's CSV diagnostic workspace.
2. 2Review the expected column count, quote findings, blank rows, and the detected input charset.
3. 3If only the charset differs, open format conversion and choose the confirmed source and output encodings.
4. 4Upload a small output file to the Import Set, inspect staging rows, and only then run the full transform.

Verify staging rows before transforming

• Every data row has the same number of fields as the header after parsing quotes.
• The selected charset renders names, ticket numbers, and non-ASCII text correctly.
• The local input and output row counts reconcile before any transform exclusions.
• The Import Set preview maps the intended fields and the transform log has no unexpected coalesce matches.

• Diagnose CSV column counts and quoted fields →Review structural findings before changing a value or header.
• Check the CSV character encoding →Choose the source encoding from the preview instead of guessing from the country.
• Split a large CSV into traceable batches →Keep the header and reconcile every output row.

Handle transform errors as a ServiceNow branch

When the CSV is structurally sound but target records are wrong, inspect transform maps, reference lookups, mandatory fields, and coalesce keys. Changing the delimiter again will not fix a semantic mapping error.

• Select the columns required by the template →Remove export-only fields while keeping all data rows.
• Split a large CSV into traceable batches →Keep the header and reconcile every output row.
• Prepare a Tableau Prep CSV after source checks →

Hand ServiceNow a reproducible import file

Keep the original file, diagnostic result, converted copy, and Import Set run number together so the next load can be compared rather than guessed.