Guide

Data quality tool: score, explain and fix your data

A data quality tool grades a dataset across completeness, uniqueness, validity, timeliness and more — with no rules to write and no setup. The AI copilot proposes the checks; a deterministic engine computes every score, so the result is exact and auditable.

Data quality, in seconds: drop in a file and get a grade out of 100, every dimension assessed, the biggest issues ranked, and real failing rows behind each one — not a vague red/green.

How it works

1 · Drop a fileCSV, Excel, JSON or a live connector — no pre-formatting.

2 · ScoreA deterministic engine grades 10 data-quality dimensions and runs rule checks.

3 · FixSee failing examples, apply guided fixes, and save rules for next time.

What you get

Scored across 10 dimensions — completeness, uniqueness, validity, consistency, timeliness and more.
Rule checks with evidence — every failing rule shown with real sample rows and a fit %.
Anomaly & outlier detection — robust z-scores and distribution drift catch what rules miss.
AI-authored checks — hand it your data dictionary or business rules; the AI writes the right checks.
Guided fixes — clean obvious issues and get a corrected file back.
No code — a business analyst, QA or ops user runs it directly.

Data quality tool vs. manual spreadsheet checks

Manual data-quality checking means hand-built formulas that break on the next file and leave no audit trail. A data quality tool scores every dimension deterministically, explains each failure, and keeps a log — so the same check is repeatable and trustworthy every run.

This is one of 20+ checks in AI data validation — the same engine also runs reconciliation, data quality, profiling, document compare and governance. For sensitive data, the full dataset never leaves your server; see the security page.

FAQ

What is a data quality tool?

A data quality tool measures how fit-for-use a dataset is — completeness, uniqueness, validity, timeliness and more — and flags the records that fail each check. AI DataValidator scores 10 dimensions, runs rule checks with real failing examples, and lets an AI copilot author the checks, while a deterministic engine computes every number.

Do I need to write rules or code?

No. The tool auto-infers checks from your data, and you can hand it a data dictionary or business rules in plain English for the AI to turn into checks. A non-technical analyst can run a full assessment in minutes.

How is the data quality score calculated?

A deterministic engine scores each dimension from the actual data — never an AI guess — and combines them into a 0–100 grade, with the biggest issues ranked so you know what to fix first.

Can checks run automatically on new data?

Yes. Save your approved rules and they auto-apply to every future file of the same shape, and you can schedule a run so the report emails itself.

Try the data quality tool free

Score any dataset across 10 dimensions, see exactly what to fix, and put it on autopilot.

Start free — 7 days, full access