  Big Data are huge amounts of digital information that are automatically
accrued or merged from several sources and rarely result from properly planned
surveys. A Big Dataset is herein conceived of as a collection of information
concerning a finite population. We suggest selecting a sample of observations
to get the inferential goal. We assume a super-population model has generated
the Big Dataset. With this assumption, we can apply the theory of optimal
design to draw a sample from the Big Dataset that contains the majority of the
information about the unknown parameters.
