AnyTool
Your files never leave your device. All processing happens locally in your browser.

How do I check the quality of a CSV dataset?

Paste your CSV into AnyTool's Data Quality Scorecard. It parses the data with a proper RFC-4180 parser, profiles every column (inferred type, fill rate, distinct values, type purity), and scores the dataset on four dimensions — Completeness (empty cells), Validity (values matching their column type), Consistency (type uniformity), and Uniqueness (duplicate rows) — combined into a weighted overall grade. It lists concrete findings (low-fill columns, mixed types, duplicate rows) and exports a per-column report as CSV. Everything runs in your browser — nothing is uploaded.

  • Per-column type detection, fill rate, distinct count & purity
  • Four scores: Completeness, Validity, Consistency, Uniqueness
  • Concrete findings + downloadable CSV report
  • 100% in your browser — no upload, no signup

What is

Data quality scoring

Data quality scoring measures how fit-for-use a dataset is across dimensions such as completeness (missing values), validity (values conforming to their expected type), consistency (uniform formats/types), and uniqueness (no duplicate records). A scorecard profiles each column and combines these into an overall grade. Client-side scoring does this in the browser without uploading the data.

File Tools

Related terms

data profilingcompletenessvaliditydata cleansingcolumn profiling

How to Score CSV Data Quality

Profile and grade a dataset entirely in your browser.

20 secWeb browser
  1. 1

    Paste CSV

    Paste your CSV with a header row. Scoring runs live.

  2. 2

    Review scores

    Read the overall grade, the four dimension scores, and the per-column profile.

  3. 3

    Export

    Copy the summary or download the per-column report as CSV — nothing is uploaded.

Result: A scored data-quality report

Frequently Asked Questions

With AnyTool, yes — the file is parsed and scored in your browser and never uploaded.

All profiling and scoring happen client-side, so confidential datasets never leave your device, unlike upload-based data-quality services.

A weighted blend of completeness, validity, consistency and uniqueness across all columns.

Each column is profiled for type, fill rate and type purity; the dataset score weights completeness and validity most, then consistency and uniqueness, into a single grade.

Yes — it flags low-fill columns, mixed-type columns, constant columns and duplicate rows.

Each column shows its inferred type, fill rate, distinct count and validity, and the findings list highlights the biggest issues; you can export the full per-column report as CSV.

Detailed Explanation

Methodology

How the Data Quality Scorecard Works

AnyTool profiles and scores a dataset entirely in the browser. The CSV is parsed with PapaParse (RFC-4180, so quoted fields are safe), then every column is profiled: each non-empty cell is classified (boolean, integer, number, email, date, or text), giving the column a dominant inferred type, a fill rate, a distinct-value count, and a type-purity percentage. Numbers are classified before dates so an ID column of 5-digit numbers is never mistaken for an Excel-serial date, and date validity reuses the project's UTC date parser. Four dimensions are scored 0–100: Completeness (share of non-empty cells), Validity (cells matching their column's inferred type; free-text columns are not penalised), Consistency (average per-column type purity), and Uniqueness (share of non-duplicate rows). These combine into a weighted overall grade (completeness and validity weighted most). The tool lists concrete findings — low-fill columns, mixed-type columns, constant columns, duplicate rows — and exports a per-column report as CSV. Nothing is uploaded.

  • Runs client-side — the dataset is never uploaded
  • RFC-4180 parsing + per-column type inference
  • Fill rate, distinct count and type purity per column
  • Four scores: Completeness, Validity, Consistency, Uniqueness
  • Numbers classified before dates (no ID-as-date false positives)
  • Concrete findings + downloadable CSV report; no CDN, no backend
Privacy & Security

Privacy vs Upload-based Profiling Tools

Most data-profiling and quality tools upload your spreadsheet to a server, which is a non-starter for confidential customer, financial or health data. AnyTool profiles and scores everything locally in the browser, so the data never leaves your device, there is no row cap behind a signup, and it works offline after first load. You see exactly how each column was typed and scored rather than trusting an opaque backend.

Data-quality scoring: AnyTool vs typical services
CapabilityAnyToolTypical services
Data handlingIn your browserUploaded to a server
Per-column profilingType, fill, distinct, purityVaries
Scored dimensions4 + overall gradeVaries
Report exportCSV, freeOften paywalled
Works offlineYes (after load)No

AnyTool is a privacy-first client-side scorecard — your dataset is profiled locally and never uploaded.