Automated Data Quality Checks Without Uploading Your Data Anywhere

The privacy angle is the whole point of this tool. If you're cleaning healthcare data or anything with PII, you can't upload it to a random website. Period. Every SaaS data quality tool requires you to trust them with your respondent-level data. I didn't want that trade-off, so I built the processing to run entirely in your browser.

Upload a CSV. The tool parses it locally using PapaParse, runs the quality checks in JavaScript on your machine, and gives you results. The file never hits a server. Close the tab and it's gone.

What it checks

Speeders: flags respondents whose total survey duration falls below a threshold (configurable, default is one-third of the median). Straightliners: detects rows where grid questions have identical responses across all items, indicating the respondent just clicked straight down the column. Duplicates: checks for duplicate entries by matching on configurable key fields (email, IP address, respondent ID). Outliers: statistical outlier detection on open-ended numeric responses. Missing data: reports the percentage of missing values per question and per respondent.

The composite score combines all five checks into a single 0-100 quality rating with a breakdown showing how each check contributed. Respondents below your quality threshold are flagged for review or removal.

It's not a replacement for a full data processing workflow. But for a quick quality pass before you start analysis, it catches the obvious problems in about 30 seconds.

Tech stack

React 18.2 + Babel CDN. PapaParse handles CSV parsing. All quality algorithms run in client-side JavaScript. Zero server calls. Zero data transmission. The only external resource loaded is the PapaParse library from a CDN.