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Clean, standardise, and prepare messy datasets so they're ready for matching, analysis, or pricing optimisation.
| Status | Name | Date Joined | Detected Issue |
|---|
TidyMonk turns recurring data cleanup into a repeatable, reliable process, so teams can focus on analysis rather than preparation.
Work with datasets ranging from thousands to millions of rows
Have analysts or business users who need to clean data without programming
Want to reduce dependency on data engineering for routine preparation
Work with complex pricing, product, or supplier data
Spend too much time cleaning spreadsheets
Need consistent datasets across multiple sources
Common users include pricing managers, product managers, and data or analytics teams across procurement, pricing, operations, and IT.
Scans incoming datasets and flags data quality issues
Cleans and standardises values using consistent rules
Applies the same logic across files to ensure repeatability
Detects missing values, duplicates, format mismatches, and inconsistencies
Outputs clean, analysis-ready data without manual rework
TidyMonk replaces:
TidyMonk reduces the time, cost, and risk associated with recurring data preparation.
TidyMonk turns clean-up into a reliable, repeatable process — not a recurring manual task.
TidyMonk sits between data collection and analysis.
It prepares incoming data before it's:
Once the data is clean and consistent, everything downstream works better.
Simple annual pricing based on team size and data volume.
Not sure which plan fits? Tell us how often you receive files and from how many sources.
| Task | Traditional Approach | With TidyMonk |
|---|---|---|
| Cleaning a 100K-row dataset | Hours to days of manual work | Minutes to hours |
| Identifying duplicates | Manual review or custom scripts | Automatic detection |
| Standardizing formats | Tedious find-and-replace operations | Bulk transformations |
| Handling missing values | Row-by-row decisions | AI-suggested strategies applied in bulk |
Your data deserves enterprise-grade protection
TidyMonk is built on more than 20 years of experience working with real-world datasets used for pricing, analysis, and operational decision-making.
It reflects how data actually arrives:
Data comes from suppliers, partners, internal systems — each with their own format
Dates, currencies, units, column names — nothing is ever standardised
Problems don't disappear after one fix — they come back with every file
Instead of one-off clean-ups, TidyMonk focuses on repeatability, transparency, and control — so data preparation no longer becomes a bottleneck.
See how TidyMonk works in practice — or share a sample file to see how it handles your data.
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