Social media data for example, like many other internet-based sources of big data, are usually based on a biased sample of the population; now-fashionable media-based indicators (of confidence, say, or political trends) are often employed with scarcely a thought for this fact.
Relatedly, the careless use of massive amounts of rough data will sometimes result in an exceptionally good in-sample fit, especially with non-parametric or machine learning approaches, but a poor performance out of sample (this is sometimes called the ‘overfitting plague’).