This article was originally published on PolicyHub (July 3, 2017).
The rapid development of information and communication technologies (ICT) is significantly changing our data landscape, and influences everything – from our daily lives, to business, science and public governance.
Data explosion is the term that describes the contemporary state of data production. New (and usually networked) ICT devices (so-called new media, internet of things) are just some of the factors that have contributed to the growing volume and variety of available data. Almost every person, company, organization or institution produces data on a daily basis, using computers, smart phones, smart TVs, self-driving cars, different equipment etc. Some estimations suggest a 4,300% increase in annual data generation by 2020, meaning that data production will be 44 times greater in 2020 than it was in 2009.
In that sense, the new technologies that have emerged have created the possibility – and also the need – for more sophisticated manipulation and analysis of data. However, coping with data has become increasingly challenging. The new data reality brings many challenges for traditional approaches to empirical research and data analysis, making it clear that the ‘new reality’ cannot be met without new, technology-driven, techniques. On the other hand, awareness of new technological capacities and opportunities is creating growing demand for more sophisticated forms of data usage such as real-time analytics, automated data processing and decision-making through machine learning and the like.
This gap between the new opportunities that have emerged from contemporary data and the technology landscape, and the old analytical techniques, has recently been filled with so-called data science. Continue reading Data Science: The Next Frontier for Data-Driven Policy Making?