Changes you can inspect.
The local cleaner produces the facts. The final review only prioritises those facts.
Free data utility · No signup
CLEAN MESSY DATA.
KEEP EVERY CHANGE VISIBLE.
Fix spacing, blank tokens, casing, obvious duplicates, clear date formats and category variants. Preview every transform, undo anything, and save the cleanup as a recipe you can run again next time.
Preview everythingNothing changes silently
Stay reversibleUndo · redo · export a copy
Repeat the cleanupSave and replay the recipe
Data Cleaner & Normaliser
PREVIEW FIRST.
APPLY SECOND.
The raw rows stay in your browser. The tool profiles the dataset, proposes conservative fixes and lets you preview the result before anything is exported.
Drop in CSV or Excel
CSV, XLSX, XLS or ODS. The file is parsed locally. Up to 100,000 data rows per sheet; larger sheets are rejected rather than silently truncated.
Preview
Add a transformlocal only
Clean-up report
WHAT CHANGED.
WHAT STILL NEEDS YOU.
Every step is visible.
Exported files are new copies. This tool never writes back into the file you uploaded. CSV downloads also neutralise spreadsheet-formula prefixes in text cells.
Built for real exports
CLEAN THE ROUTINE MESS.
REVIEW THE REST.
Good cleaning is reversible. You should know what changed, why it changed and what the tool deliberately refused to guess.
Find the obvious mess.
Whitespace, blank tokens, email-domain casing, exact duplicates, clear date formats and obvious category variants are detected without sending the raw records away.
Preview every transform.
Suggested steps are not silently applied. Ambiguous dates and risky fuzzy matches are surfaced for review rather than guessed.
Save the recipe.
Download the operation recipe and load it against the next export. Matching columns are remapped safely by header; a recipe is blocked if its target columns cannot be identified without guessing.
FAQ
WHAT IT WILL AND
WON’T GUESS.
The cleaner is deliberately conservative. It is designed to make useful fixes without quietly changing the meaning of your data.
Does the raw dataset leave my browser?
No. The file is parsed and transformed in the browser. The optional review receives aggregate issue counts and generic roles such as “email column” or “category column”, not raw rows or cell values.
Will it merge similar values automatically?
Only obvious variants such as differences caused by whitespace, casing or simple punctuation are proposed. Riskier fuzzy matches remain suggestions that need a human decision.
What happens with ambiguous dates?
They are flagged. A value such as 08/01/2026 can mean different dates in different locales, so the tool does not silently choose one.
Why save a cleaning recipe?
If the same CRM, accounting system or supplier sends you a messy export every month, the recipe lets you replay approved transformations. Matching columns are remapped by header when the match is unambiguous; missing or ambiguous targets block the recipe rather than guessing.