Is Your Data Actually Ready for AI?
Most AI projects fail because of bad data — not bad models. This checklist walks you through the same 6 dimensions our free analyzer uses, so you can audit your dataset in under 15 minutes.
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What's inside
A preview of the 6 dimensions covered in the checklist.
Structure
Is your data consistently formatted and machine-readable?
- Consistent column names and types?
- No mixed data types in a single column?
- Headers on every file?
Completeness
Are there enough records — and are they filled in?
- Null rate under 5% for key fields?
- Enough rows to train or fine-tune?
- No silent truncation?
Quality
Is the data accurate, consistent, and free of noise?
- Duplicates identified and handled?
- Outliers reviewed (not just removed)?
- Ground-truth labels validated?
Distribution
Does your data reflect real-world patterns evenly?
- No severe class imbalance?
- Training data matches production distribution?
- Time-based splits tested?
AI Readiness
Is the data governed, documented, and legal to use?
- Lineage and provenance documented?
- PII identified and handled?
- Licensing cleared for model use?
Field Statistics
Do you understand the statistical properties of your fields?
- Cardinality measured for categoricals?
- Range and variance checked for numerics?
- Date/time fields parsed consistently?
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