I think &quot;big&quot; data is being confused with &quot;ubiquitous&quot; data in this article. Larger datasets will always lead to more statistical confidence in a conclusion you make from the data. The article does a great job of explaining the caveats to this (data skews, misuse of stats, external factors), but those issues exist with small data too. In other words, this isn&#x27;t about the volume of data. I think there are two real and different issues at play here, and both come instead from the ubiquitousness of data nowadays:<p>1. It&#x27;s become easier to do more experiments, so even experts are more likely to produce some bad conclusions.<p>2. Data has become much more accessible, so people without rigorous stats backgrounds have an easier time abusing the hell out of stats on datasets.