After all the hype, there’s big problems for big data
There may even be a public backlash against related findings, warns Professor Ian Scott
A few years ago, big data seemed like the Holy Grail — a way for computer programs to find meaning in datasets too big for traditional analysis.
Big data would “transform medicine” (said a 2016 NEJM article) or “redefine statistics” (MJA, 2013). It was the “likeliest solution to future scientific advances” (BMJ, 2017).
