Free Data Quality Self-Check Template

Quick answer

Self-check data quality on five dimensions — completeness, accuracy, consistency, timeliness and validity — with 25 weighted statements and an AI PDF report that ranks the weakest dimension first.

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About this template

Data problems surface as decisions nobody trusts. This self-check scores twenty-five weighted statements across five dimensions — Completeness, Accuracy, Consistency, Timeliness and Validity — as the team answers how the data actually behaves rather than how it is documented. Each run returns an AI PDF report ranking the weakest dimension and what to fix first, which is also the honest way to brief a data quality programme.

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What's Included

Everything you need to run this template.

1

Five quality dimensions

Completeness, accuracy, consistency, timeliness, validity.

2

Twenty-five statements

Scored on how the data behaves in practice.

3

Banded report

The AI PDF ranks the weakest dimension first.

4

Briefing evidence

A defensible starting point for remediation.

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How It Works

From copy to deliverable in four steps.

1

Use this template

Copy the self-check into your FormLM workspace — free.

2

Answer as the team

Score how the data behaves, not what is documented.

3

Get the report

Five dimensions banded, weakest named first.

4

Re-run per period

Same statements each quarter show the fix working.

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Who Is This For

Pick your role — see how it fits your workflow.

1

Data and insight leads

Know which dimension to fix.

2

Analytics teams

A baseline before tooling spend.

3

Governance owners

Evidence for a data quality plan.

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Key Features

What makes this template work as a professional deliverable.

Five quality dimensions
Twenty-five weighted statements
Banded results per dimension
Personalized AI PDF report
Re-runnable per quarter
1-click copy to workspace

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Sample Questions Inside

A preview of real questions — the full version adds scoring and a personalized report per respondent.

All required fields in my datasets are populated (1-5)
No critical records are missing from my data sources (1-5)
Every entry has all mandatory attributes filled (1-5)
I track field completion rates systematically (1-5)
Missing data is flagged and remediated promptly (1-5)
My data values match the original source documents (1-5)

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Frequently Asked Questions

What do you mean by data quality, concretely?

Five dimensions: completeness, accuracy, consistency, timeliness and validity — each scored on how the data behaves.

Why twenty-five statements?

Five items per dimension is the point where each band carries weight without diluting into noise.

Who should answer — the team or the owner?

The people who touch the data. Owners score what should happen; the team scores what does.

What does the AI report rank?

The weakest dimension first, with bands per dimension and the interpretation to brief a fix.

Should it be repeated?

Quarterly on the same statements — otherwise improvement is indistinguishable from optimism.

Does each dataset cost something?

No — copy one free self-check per source, team or quarter.

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