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Data cleaning examples: six real jobs, before and after

Six files that turn up over and over, what is wrong with each one, and the exact rows the engine proposes to change. Every table below is the same diff the demo produces.

6 jobs, each before and after

18 rows, exactly as the diff states

0 invented figures, anywhere

01 RevOps, before a platform move

CRM migration cleanup

Six years of accounts and contacts, entered by four generations of sales team. The same company exists three times under three spellings, and the migration will faithfully carry all three across.

After

Duplicate accounts merged into the most complete record, with an audit log the AE team can read before they lose a record they were using.

Original rows Proposed Rule
Ridgeline Partners / Ridgeline Partners LLC One account, the fuller row kept Fuzzy company match, legal suffix
marcus.hall@ridgeline.com / m.hall@ridgelinepartners.com Both kept on the merged record Cluster merge, contact fields preserved
Last Contacted 4-Mar-26 / 03/04/2026 2026-03-04 Date format

Every one of those rows is a proposal you approve or reject before anything is written.

02 Marketing ops, the week before a send

Campaign list hygiene

A list assembled from a webinar export, a content download and a purchased segment. The same person appears with a work address, a personal address and a typo, and the bounce rate is about to tell everyone.

After

One row per person, addresses lowercased and trimmed, undeliverable strings flagged rather than silently sent to.

Original rows Proposed Rule
Jose.Munoz@Acme.com jose.munoz@acme.com Whitespace and email casing
j.munoz@acme.com (same person, second row) Cluster, one row kept Fuzzy name and company match
sarah@@northwind.co Flagged, not sent Invalid address shape

Every one of those rows is a proposal you approve or reject before anything is written.

03 A finance or business analyst, at month end

Multi-source financial reconciliation

Three exports from three systems. One writes dates day-first, one month-first and one as a spreadsheet serial number. Amounts arrive as text with currency symbols, and negatives are in brackets.

After

Every date in ISO 8601 and every amount a plain number, so the three files finally join and the totals tie out.

Original value Proposed Rule
46085 2026-03-04 Spreadsheet serial date
$12,400.00 12400.00 Currency format
(1,250.50) -1250.50 Parenthesised negative

Every one of those rows is a proposal you approve or reject before anything is written.

04 Demand gen, the Monday after the conference

Event and lead capture cleanup

A badge-scan export where names, companies and emails were typed by hand at a booth. Everything is shouted in capitals, half the accents are broken, and the same visitor was scanned twice.

After

Names recased and repaired, duplicate scans clustered, and the list usable the same morning instead of at the end of the week.

Original value Proposed Rule
JOSE MUñOZ Jose Muñoz Encoding repair and casing
ACME CORP . Acme Corp Whitespace and punctuation
Two scans, same badge One row, both timestamps kept Duplicate cluster

Every one of those rows is a proposal you approve or reject before anything is written.

05 Operations, after an acquisition

Supplier and product catalog merge

Two vendor lists that describe overlapping products under different SKUs and different supplier spellings. Nobody knows how many suppliers there really are, so nobody can negotiate.

After

Supplier names standardized and matched, SKU casing and padding made consistent, and the real supplier count visible for the first time.

Original value Proposed Rule
northwind trading co. / Northwind Trading Company One supplier Fuzzy company match
sku-00421 / SKU 421 SKU-00421 Identifier casing and padding
0042 00042 Leading zero restored

Every one of those rows is a proposal you approve or reject before anything is written.

06 Ecommerce or logistics, before a mail house run

Address file standardization

A shipping file where states are written four ways, postcodes lost their leading zeros in a spreadsheet, and the country column mixes codes and names.

After

One form per state and per country, postcodes restored to their real length, and a file a validation service or a mail house will accept.

Original value Proposed Rule
Calif. / CALIFORNIA / california CA US state standardization
2139 02139 Leading zero restored
United States of America / usa US Country standardization

Every one of those rows is a proposal you approve or reject before anything is written.

07 What the six have in common

Nobody made these files badly on purpose

Every one of them was produced by a system doing exactly what it was told, over several years, by people who each had a reason for typing it that way.

The damage is entered, not introduced

A booth scan, a form with no validation, an export through a spreadsheet. The file is the sum of every hand that touched it.

The fix has to be reviewable

Somebody will ask why a record moved. A proposal you approved answers that; a script that ran overnight does not.

It happens again next quarter

The same export arrives with the same faults, which is why the work is worth saving as a recipe rather than repeating by hand.

The rules are boring and that is good

Dates, casing, leading zeros, legal suffixes. Nothing here needs to be clever, it needs to be applied consistently and shown to you.

08 Your file, not ours

Run one of these on a real file now

The three samples below are the messy versions of the cases above. Or drop your own CSV and see what it finds.

1. Load a file

Your file is read on your own machine. Nothing is uploaded, so nothing can leak.

Or start from a messy sample

Status

Loading the sample file.

File: CRM contact export

Rows

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Columns

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Changes

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Duplicate rows

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Date formats

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Blank emails

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Load a file to see the diff

Drop a CSV or pick one of the messy samples. Every proposed change appears here as a line you approve or reject.

Clean the file, and be able to show what you changed

Try the demo on your own CSV first. It runs in your browser, it costs nothing, and no card is required.

No card required. Your file never leaves your computer.

Clean a file