Your model can't beat your noise floor
15 June 2026 · Risto Anton Päärni · Helsinki, Finland
Most people picture an ML project as one thing: training. It isn't.
In reality a project is about 50% evaluation,
40% data cleaning, 8% integration, and
2% training. The part everyone imagines is the whole job is the smallest
sliver of it.
| Phase | Share | What it actually is |
|---|---|---|
| Evaluation | 50% | Defining what "correct" means, building the test set, scoring honestly |
| Data cleaning | 40% | Labels, dedup, reconciliation, removing contradictions |
| Integration | 8% | Wiring the model into systems that act on the output |
| Training | 2% | The part everyone pictures as the entire project |
Read the top two rows again. Evaluation and data cleaning are ninety percent of the work — and they are exactly the part an off-the-shelf model hands you nothing for.
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