Does Big Data Mean the End of the Scientific Method?
It is well-known that correlation does not imply causation. Big Data correlation models do not replace specific hypothesis testing that can be generalized. A Big Data discovered correlation can have a numerical basis but without meaning.
The gold standard in medical research is a randomized controlled trial. Although no single study is likely on its own to prove causality, randomization reduces bias and provides a rigorous tool to examine cause-effect relationships between an intervention and outcome. This is not possible with any other study design.
Big Data advocates claim that data volume replaces the need for the gold standard. Relying on correlations alone cannot replace empirical testing of causation. The axiom ‘‘with enough data, the numbers speak for themselves” is dangerous fiction, not a fact.