What is big in big data: a sampling statistician perspective

Big data users and the big data research community are expanding rapidly, while statisticians at large seem to become divided between those who are enthusiastic and those who are concerned, if not downright hostile. Is big data also a big step ahead, truly advancing our ability to extract meaningful information and actual knowledge from data? Is big data underplaying traditional statistical inference as we know it, supplanting survey methodology as a low-cost futuristic option? In this talk I will attempt to unravel the multifaceted relationship bridging big data to sampling methodology. Starting by reasoning why it should be interesting to look at big data from a sampling statistician's perspective, I will delve deeper into the somewhat ambiguous definition of big data and share some very personal considerations and views on the matter. In the process, several open questions will arise while discussing a personal selection of insights that are traceable through the vast body of statistical literature around big data and sampling methodology.