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Data quality tools, and what to compare before you buy one

Data quality tools profile, fix and monitor the data your business runs on. They differ far more than their feature lists suggest. The questions that decide it are how they match records, whether a person reviews changes, and what you can prove afterwards.

In-browser your file never leaves your computer

Every row proposed to you before it is applied

CSV log of what you approved and rejected

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01 Try it on this page

Load a messy sample and watch it work

The same engine described below, running on your own machine. Nothing is uploaded and nothing is applied until you approve it.

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 or invalid 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.

02 About data quality tools

The five questions that separate them

1. How does it match?

Exact only, or fuzzy across several fields? Exact matching leaves most real duplicates in place.

2. Who approves a change?

A tool that rewrites cells on its own is fast until the first time it is wrong in a file you already sent out.

3. What is the record of it?

Ask for the audit log as an export. If the answer is a screen you can scroll, it will not survive an argument about a number.

4. Where does the data go?

Desktop, your browser, or a vendor server. This is the question your security team will ask first.

5. What does the price scale on?

Seats, records, or connected systems. A per-seat license is expensive for occasional users; volume pricing punishes a one-off big migration.

How the categories compare

Spreadsheet Open-source desktop CRM-native app Enterprise platform DataUntangler
Runs without installing Yes No Yes, inside the CRM Varies Yes, in your browser
Fuzzy matching No Yes Yes Yes Yes
Row by row approval No Partly Yes Varies Yes
Exportable audit log No No Varies Yes Yes
Works on a raw CSV Yes Yes No Yes Yes
Time to first result Minutes An afternoon Days Weeks Under a minute

Category level comparison, not a product scorecard. Check any specific product against its own current documentation.

What a data quality program needs beyond a tool

Buying software does not fix data quality on its own. The teams that keep files clean agree on a definition of a duplicate, decide which system is the source of truth for each field, and clean on a schedule rather than in a panic before a migration. That is also why an analytics platform bought for the prep step tends to look oversized on renewal, which is the case set out on the Alteryx alternative page.

A tool helps with the last mile: doing the work quickly and leaving evidence. Look for one that produces an artifact you can attach to a ticket, not just a cleaner file. The two capabilities that decide most evaluations are fuzzy matching and entity resolution; the habit around them is data hygiene, and the data cleaning tool here is the part you can try before any of it.

Test every tool on the same file

The fastest way to compare data quality tools is to give each one the same ugly export and read what comes back. Build the test file from your own data, or copy the shape of the one below: an eight row customer master from an accounting system, with the faults a real one has. Then count what each tool found, what it changed without asking, and what it can show you afterwards.

We ran ours through this engine. It proposed 27 field fixes and one duplicate pair and flagged two rows it would not guess about. Sixteen of the fixes were currency values ($25,000.00 to 25000.00, 4812.5 to 4812.50), three were country spellings (USA, US and U.S. to United States), three were dates in four formats, two were states, one was a ZIP code that had lost its zero (4101 to 04101), one was an encoding repair (Bluebonnet Café to Café) and one was an email in capitals.

Write down the misses as well. Cedar & Stone Builders LLC and Cedar and Stone Builders had two different billing emails, and this engine did not propose them as one customer, because an ampersand against the word and plus a different email stays under its threshold. A good trial is one where you know exactly which pairs a tool misses before you buy it. The matching rules and their limits are written out on data deduplication tools.

What to score in a data quality tool trial

Keep the scorecard short and tied to the file. A feature list will tell you every product matches and standardizes; the file tells you how well, and what it costs you when it is wrong.

Check What to look for What this engine did on the test file
Duplicates found Same email in different case, legal suffixes, missing emails Harbor Point Marine Inc. and Harbor Point Marine proposed on the shared email
Duplicates missed Pairs you know are the same that it did not propose Cedar & Stone and Cedar and Stone, different emails
Changes made without asking Should be zero on a file that feeds a ledger Zero, all 27 fixes were proposals
Values it refused to guess Invalid emails and blanks flagged, not invented granitepeak@yahoo flagged, one blank billing email counted
Evidence afterwards A file you can attach to the ticket CSV audit log with original, proposed, rule and decision
Where the file went Your security review will ask Nowhere, the demo runs in the browser

Run the same file through every tool on your shortlist and fill in the last column for each one.

Who buys a data quality tool for files

This category is bought by the person who has to stand behind a number: a controller cleaning the customer master before an ERP move, a RevOps lead consolidating CRM exports after an acquisition, or an analyst whose dashboards are fed by spreadsheets from three teams. They do not need a platform with a steward queue; they need clean files this week and a record of every change.

The Analyst plan runs unlimited files of up to 25MB each, and Enterprise puts several people on one invoice with a DPA and purchase orders. See pricing, or run the demo above on your own export first.

03 Read it off a real file

A real engine run on an eight row customer master

Column Before Proposed Rule
Credit Limit $25,000.00 and 25000 25000.00 and 25000.00 Currency format
Country USA, US, U.S. United States Country standard
Last Invoice Date 09/30/2025, Sep 12 2025, 8/1/2025 2025-09-30, 2025-09-12, 2025-08-01 Date format
Billing State Maine, Texas ME, TX State standard
Zip Code 4101 04101 Leading zero
Company Bluebonnet Café Bluebonnet Café Encoding repair
Billing Email granitepeak@yahoo Not changed, flagged Invalid address shape

Every proposal waits for approval. The single duplicate pair, Harbor Point Marine, was proposed on the shared billing email with high confidence.

04 How the evaluation goes wrong

Three ways a tool evaluation reaches the wrong answer

The shortlist is usually decided by a demo and a feature grid. Neither one tells you what the tool does to your own export.

How this one is priced

The demo runs on their file

A prepared dataset shows the matcher at its best. Ask to load your own export instead, and watch what it does to the columns your team actually argues about.

The feature grid hides the difference

Every product in the category ticks matching, cleansing and monitoring. What separates them is whether a person approves a change and whether anything records it.

The price scales on the wrong unit

Records, credits, connectors or seats. If the unit is not the one your work grows in, year two costs a multiple of year one for the same job.

What to get in writing before a pilot

How it matches, who approves a change, what the record of it is, where the data goes, and what the price scales on. Five answers, from every vendor on the list.

05 Before you run it

Questions about data quality tools

Is a data quality tool the same as a data catalog?
No. A catalog documents what data you have and where it lives. A data quality tool inspects and fixes the values inside it. Larger organizations run both.
Where does DataUntangler fit?
In the gap between a spreadsheet and a platform: browser based, works on the file you already have, and produces a reviewable diff plus an audit log.
How do I evaluate data quality tools?
Run the same export from your own systems through each one. Count the duplicates it found and the ones it missed, check that nothing changed without your approval, and ask for the record of the changes as a file. A vendor demo on their own dataset tells you none of that.
What should a data quality tool fix automatically?
On data that feeds reporting or accounting, nothing without a review. Formatting fixes such as dates, currency and state codes can be approved in bulk, while merges and anything ambiguous should be checked one at a time. Values it cannot know, such as a malformed email, should be flagged rather than guessed.
Do I need a data quality platform or a file tool?
A platform makes sense when data has to stay clean across live systems with rules running every day. If the work arrives as exports, imports, migrations and quarterly lists, a file tool that shows each change and logs it does the job with no implementation project.
06 What it costs

Plans for when the file is bigger than the demo

Yearly billing saves 50 percent. There is no free plan, and no card is needed to use the browser demo above.

Yearly billing saves 50 percent, half the monthly price.

Switch to yearly and save 50 percent.

Analyst

Self-serve

One person with files to clean, as many as they like.

$29$59/mo

Billed $348 a year Billed monthly

Buy Analyst, yearly Buy Analyst, monthly
  • Unlimited files
  • Files up to 25MB, about 100,000 rows
  • Exact and fuzzy duplicate detection
  • Dates, numbers, currencies, encoding and casing fixed
  • Every change reviewable before you download
  • Cleaned CSV and a change log, both downloadable
  • Runs in your browser: files never leave your machine
  • Email support

Enterprise

Several people on one invoice, a DPA on request, priced per seat.

$49$98/seat/mo

Billed $588 a seat a year, from 2 seats ($1,176) Billed monthly per seat, from 2 seats ($196)

Buy Enterprise, yearly Buy Enterprise, monthly
  • Everything in Analyst
  • Several people on one invoice
  • DPA on request
  • Invoicing and purchase orders
  • A named contact for support

Payment is by card through our payment provider, monthly or yearly, and you can cancel from your account at any time. The free try is one file of your own, up to 5MB, in the browser demo. Already paid? Sign in.

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