# Data Readiness Checklist

## Purpose and relevance
- [ ] The prediction or task target is clearly defined.
- [ ] Data represents the intended users, time period and environment.
- [ ] Inputs will be available when the system is actually used.

## Access and governance
- [ ] The data owner is identified.
- [ ] Collection and use have an appropriate legal and organizational basis.
- [ ] Consent, licensing and retention conditions are documented.
- [ ] Sensitive data is identified and protected.

## Quality
- [ ] Missing values and invalid records are measured.
- [ ] Duplicate records and inconsistent formats are handled.
- [ ] Labels have a clear definition and quality review.
- [ ] Class imbalance and rare but important cases are understood.
- [ ] Potential proxy variables and historical bias are reviewed.

## Evaluation readiness
- [ ] Training, validation and test boundaries prevent leakage.
- [ ] Time-based data uses an appropriate chronological split.
- [ ] Important groups and operating conditions appear in test data.
- [ ] A future data-quality monitoring owner is assigned.

## Decision
- Ready / conditionally ready / not ready:
- Required improvements:
- Owner and review date: