What does the data transformation recorder produce?
Apply an explicit sequence of supported field transformations and preserve exact before-and-after values and steps.
Use the exact local files and task-specific inputs listed below. Preparation and review stay in this browser. Inspect all findings before preparing the finalized pack.
What do you need before you start?
- Define the authorized source population and your review rules.
- Keep the unchanged original files and record the snapshot and exclusions.
- Review missing and invalid inputs before preparing the finalized pack.
What information do you enter?
Select the actual local sources and freeze the task-specific inputs below. Keep source files and complete findings private.
- One exact-text CSV, one-sheet XLSX or dataset JSON source.
- Approved transformation steps. JSON array, 1 to 50 steps. Actions are rename (field,to), drop (field), trim/upper/lower (field), replace (field,find,with). Replacement is literal, not a regular expression.
| Field | What to enter | Fictional example |
|---|---|---|
| Approved transformation stepsRequired | JSON array, 1 to 50 steps. Actions are rename (field,to), drop (field), trim/upper/lower (field), replace (field,find,with). Replacement is literal, not a regular expression. | [{"action":"rename","field":"Status","to":"State"},{"action":"upper","field":"State"}] |
What you can download
Every result must identify its supplied facts, assumptions and unresolved items.
| Free result | Included downloads |
|---|---|
Enter your information, inspect the on-screen result and keep a browser backup. Editing and direct copies of your entered information stay free. |
These supported outputs are free. No checkout is required. |
Fictional review report (PDF). Editable review (DOCX). Complete fictional pack (ZIP). Requires tailoring and responsible review. Samples use the finalized renderer.
How does the data transformation recorder work?
- 1Select the actual sources
One exact-text CSV, one-sheet XLSX or dataset JSON source.
- 2Freeze the review rules
Apply approved steps in order to a copy. Reject unknown fields, colliding names and unsupported actions before returning any result. Keep the original dataset, complete transformed dataset and every affected cell in the audit.
- 3Inspect complete findings
Review all source-linked results and unresolved items. Free JSON and CSV preserve complete results.
- 4Keep recoverable work
Browser-local inputs and exact source files survive reload. Restore a validated exact-byte backup ZIP or explicitly approved private cloud revision. Earlier generic workspace keys, original files and historical purchases remain separate and preserved. Download preserved earlier strings and bytes before changing devices.
- 5Prepare the finalized pack
Prepare seven files, then download them free. Review the fictional sample below.
Method and sources
Apply the steps above to the supported inputs. Use the listed source sections to review the rule basis, assumptions and limits.
- Common Format and MIME Type for Comma-Separated Values (CSV) FilesCSV record, field and quoting conventions. This source does not specify customer schemas, matching rules, checksum arithmetic, sampling quality or import acceptance. Section 2. Definition of the CSV Format.RFC Editor. Reviewed 2026-10-08.
- Secure Hash StandardSHA-256 digest specification for exact source-byte and delivered-file checks. It does not establish authenticity or validate the named review rules. Section 6.2. SHA-256.National Institute of Standards and Technology. Reviewed 2026-10-08.
Common questions
What information does the data transformation recorder need?
Enter one exact-text CSV, one-sheet XLSX or dataset JSON source; approved transformation steps. JSON array, 1 to 50 steps. Actions are rename (field,to), drop (field), trim/upper/lower (field), replace (field,find,with). Replacement is literal, not a regular expression. Define the authorized source population and your review rules.
What does the data transformation recorder produce?
Complete source-linked on-screen review and free JSON/CSV results. Seven-file finalized pack. Formal PDF and DOCX, complete Excel review, CSV ledger, exact parsed sources and inputs JSON, delivered-file SHA-256 manifest and instructions. Sampled or transformed output dataset where applicable. Exact original files and browser backup ZIP remain separately downloadable. Review unresolved findings and limitations before use.
Who makes the final decision?
A responsible person reviews the result. Apply approved steps in order to a copy. Reject unknown fields, colliding names and unsupported actions before returning any result. Keep the original dataset, complete transformed dataset and every affected cell in the audit.
Is this tool free?
Yes. The on-screen result and listed downloads are free. No checkout is required. Keep local backups and review the stated method and limits.
Can I use the data transformation recorder for this task?
Preserve the steps from source to output. Apply approved steps in order to a copy. Reject unknown fields, colliding names and unsupported actions before returning any result. Keep the original dataset, complete transformed dataset and every affected cell in the audit.
What still needs review?
Apply approved steps in order to a copy. Reject unknown fields, colliding names and unsupported actions before returning any result. Keep the original dataset, complete transformed dataset and every affected cell in the audit.
Checks do not authenticate source records, population completeness, identifier issuance, external checks, a completed import or compliance.
Use at most 5000 data rows, 50 fields, 100000 cells and 5000000 parsed characters. Up to 10 MB per source. Typed spreadsheet cells, stored formulas and multiple worksheets require an explicit text export.
Formal reports show at most 100 rows and 300 characters per displayed field. Excel and JSON preserve complete results.