Data quality tools: 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.
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 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.
2. Review every change
Nothing approved yet.
Nothing is applied to your file until you approve it, and your original file is never modified.
Proposed changes
Original Proposed
Showing the first 400 changes. 0 more are in the audit log download.
Duplicate clusters
Merge or keep both
Want this on bigger files, on a schedule, with your team?
Saved recipes, scheduled cleans and shared seats are part of the paid plans. Start with your email and we will send you a code.
3. Take the result
The downloads work without an email. The cleaned CSV contains only the changes you approved.
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.
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.
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 pricedThe 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.
Questions about data quality tools
Is a data quality tool the same as a data catalog?
Where does Datauntangler fit?
Plans for when the file is bigger than the demo
Yearly billing is two months free. There is no free plan, and no card is needed to use the browser demo above.
Yearly billing is two months free.
Switch to yearly and two months are free.
Analyst
One ops person or analyst with files to clean.
$49$59/mo
Billed $590 a year Billed monthly
- 50,000 rows a month
- Files up to 25MB
- 1 seat
- Fuzzy matching and entity resolution
- Reviewable diff and audit log export
- 3 saved cleaning recipes
- Email support
Team
RecommendedA RevOps or marketing ops team sharing the work.
$166$199/mo
Billed $1,990 a year Billed monthly
- 250,000 rows a month
- Files up to 100MB
- 5 seats
- Everything in Analyst
- Unlimited saved recipes
- Scheduled recurring cleans
- CRM connectors (Salesforce, HubSpot)
- Priority email support
Business
A data team cleaning for several departments.
$499$599/mo
Billed $5,990 a year Billed monthly
- 1,500,000 rows a month
- Files up to 500MB
- 20 seats
- Everything in Team
- API access
- Roles and permissions
- Priority email support
Enterprise
A head of data who needs it defensible across the company.
Talk to sales
Custom terms, invoicing and PO
- Unlimited rows and custom file sizes
- Unlimited seats
- Everything in Business
- SSO (SAML / Okta)
- Custom data retention
- DPA on request
- Named support contact
- Invoicing and PO
- Named onboarding
A row is one data line in a file you process, not counting the header. The browser demo is free to use and is not a plan: it reads CSV and TSV files up to 5MB on your own machine.
Related pages
- Data Cleaning Software for CSV and Spreadsheet Files
- Entity Resolution for Customer and Company Records
- Data Hygiene for Contact Lists and CRM Records
- Data Cleaning Services vs Doing It In House
- Fuzzy Matching Tool - Match Names, Companies and Emails
- Excel Data Cleaning Without Formulas or Macros
- Data Deduplication Tools That Match More Than Exact Values
- Address Standardization for Shipping and Billing Files
- CRM Data Cleansing Before a Migration or an Import
- Salesforce Deduplication on the Export, Before It Goes Back
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.