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A broad review is given of the impact of big data on various aspects of investigation. There is some but not total emphasis on issues in epidemiological research.
7 Concluding remarks
Big data enable investigations to be conducted and reliable conclusions to be drawn that would otherwise be difficult or impossible. An example is their use in pharmacoepidemiology to evaluate treatment effects (Smeeth et al, 2009; Hernan & Robins, 2016).
We have highlighted some of the challenges that arise in the use of big data. One main theme has been to emphasise the potential for overconfidence in results obtained from analyses of large data sets, due to superficially highly precise but potentially biased estimates, or due to under-estimated standard errors. The size of the data does not remove the need for appropriate study design and statistical analysis (e.g. Welch et al, 2014, Lin et al, 2004, Pullenayegum & Lim, 2016). The potential impact of unobserved and unaccounted-for dependencies must not be ignored.
We have focused primarily on big data in the biomedical field. Even within that field there are many sources of big data that we have not mentioned. Each may present special challenges and opportunities.
In summary, while the availability of big data offers many possibilities for improved understanding, the need for careful and productive use of statistical concepts is pervasive and raises many challenges.