Data·4 min read
Why Data Quality Matters for AI
An AI system can only be as reliable as the data it reasons over.
Draft article — pending editorial review.
Missing timestamps, inconsistent units, and duplicated records quietly undermine any analysis built on top of them. AI does not fix this; it can make the errors more convincing.
Validation and normalization belong at the point of integration, before data reaches dashboards or models.
Being honest about data gaps — and showing them to users — is part of building a trustworthy system.