07/01/2026
Most machine learning failures don’t happen in models. 🤖❌
They happen long before — in the assumptions teams make about their data.
When structure, quality, and behavior aren’t understood, every downstream decision becomes harder to trust. This is why foundational data clarity matters more than any algorithmic choice.
Below is a clear breakdown of the 12 data types that consistently shape how ML systems behave in real environments.
A practical reference to help teams diagnose issues early, design with intent, and strengthen the reliability of every ML workflow.
