Abstract
This chapter is an introduction to the use of data science technologies in the fields of economics and finance. The recent explosion in computation and information technology in the past decade has made available vast amounts of data in various domains, which has been referred to as Big Data. In economics and finance, in particular, tapping into these data brings research and business closer together, as data generated in ordinary economic activity can be used towards effective and personalized models. In this context, the recent use of data science technologies for economics and finance provides mutual benefits to both scientists and professionals, improving forecasting and nowcasting for several kinds of applications. This chapter introduces the subject through underlying technical challenges such as data handling and protection, modeling, integration, and interpretation. It also outlines some of the common issues in economic modeling with data science technologies and surveys the relevant big data management and analytics solutions, motivating the use of data science methods in economics and finance. Authors are listed in alphabetic order since their contributions have been equally distributed.
Cite
CITATION STYLE
Barbaglia, L., Consoli, S., Manzan, S., Recupero, D. R., Saisana, M., & Pezzoli, L. T. (2021). Data science technologies in economics and finance: A gentle walk-in. In Data Science for Economics and Finance: Methodologies and Applications (pp. 1–17). Springer International Publishing. https://doi.org/10.1007/978-3-030-66891-4_1
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