Check Dataset Health Online
Score a CSV for missing values, duplicates, row shape, and type consistency before trusting it.
Problem
A dataset looks complete, but hidden quality issues may break analysis, dashboards, or models.
What to do
A health check gives you a high-level score and a prioritized list of problems. Run it before deeper cleaning or visualization.
- 1Load the CSV.
- 2Review the health score and issue breakdown.
- 3Export the report or continue with a cleaning tool.
Use the browser tool
Dataset Health Analyzer profiles a CSV and scores it across the four things that actually break downstream work: missing values, duplicate rows, ragged row shape, and columns whose type is inconsistent from row to row. It gives you a single health score to compare datasets against each other, and a per-column breakdown showing which columns are dragging that score down and by how much — so cleaning starts with the column that matters rather than the first one in the file.
People also ask
- What counts as a duplicate row?
- A row whose every field matches another row exactly. Near-duplicates — same record with a differently formatted phone number — are not caught here; that is what fuzzy matching is for.
- Is my data uploaded to be analysed?
- No. Parsing and scoring happen in your browser. The site is a static export with no backend, so there is nowhere for the file to be sent.
- What is a good score?
- Compare rather than target. The score is most useful for ranking datasets against each other and for tracking one dataset across cleaning passes, not as an absolute pass mark.