Journal
TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE
Volume 130, Issue -, Pages 99-113Publisher
ELSEVIER SCIENCE INC
DOI: 10.1016/j.techfore.2017.07.027
Keywords
Big Data architecture; Forecasting; Nowcasting; Data lifecycle; Socio-economic data; Non-traditional data sources; Non-traditional analysis methods
Categories
Funding
- Spanish Ministry of Economy and Competitiveness [TIN2013-43913-R]
- Spanish Ministry of Education [FPU14/02386]
Ask authors/readers for more resources
The Data Big Bang that the development of the ICTs has raised is providing us with a stream of fresh and digitized data related to how people, companies and other organizations interact. To turn these data into knowledge about the underlying behavior of the social and economic agents, organizations and researchers must deal with such amount of unstructured and heterogeneous data. Succeeding in this task requires to carefully plan and organize the whole process of data analysis taking into account the particularities of the social and economic analyses, which include the wide variety of heterogeneous sources of information and a strict governance policy. Grounded on the data lifecycle approach, this paper develops a Big Data architecture that properly integrates most of the non-traditional information sources and data analysis methods in order to provide a specifically designed system for forecasting social and economic behaviors, trends and changes.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available