Socio-economic Statistics for a Complex World: Perspectives and Challenges in the Big Data Era

Abstract

This chapter addresses a topic which is gaining increasing interest in socio-economic statistics and that will play a central role in what in the future could possibly be called “information-based policy-making”. The topic is that of big data and data science and of their potential effects on next future socio-economic statistics (Landefeld 2014). Although no relevant applications have been produced yet at “official level”, the use of big data and the applications of data science methodologies are in fact opening new avenues to the way socio-economic statisticians may extract information from different data sources and provide it to decision-makers. It is surely not easy to write a chapter on this theme. The topic, “big data and data science”, is in fact a broad concept and cannot be considered as a scientific discipline yet, though it is attracting research efforts from many different sectors and many people are contributing to its development. It can be addressed from many points of view and different aspects (technological, methodological, epistemological…) could be underlined, giving different alternative pictures of the argument. Given the aim of the book, here we simply outline some basic concepts pertaining to big data, to clarify why socio-economic statisticians should be interested in this area, to help them realize its potentialities and criticalities and to stress the conceptual differences with respect to “traditional” statistical analysis. The chapter is somehow different from others in this book. It is non-technical and is based on reflections and experiences of the Author, who has been involved in didactical activities and in real projects pertaining to big data analysis and data science. As a consequence, the text may seem more “subjective” than other contributions in the volume. This is true and partly unavoidable: the attempt is to collect and share what I could learn on the topic in the last years, motivating why I think big data can open new horizons to applied statistics, in the socio-economic field.