Location
260-073, Owen G. Glenn Building
Start Date
12-15-2014
Description
Many employers expect to face a significant shortfall of workers with data science skills in the coming decade. This panel focuses on the opportunities and challenges this poses for the Information Systems community. Specifically, the panel focuses on three key questions at the nexus of data science, skills, and IS: a) characterizing the changes in skill demand from industry in a variety of global economic contexts, b) evaluating the role of IS departments in educating the next generation of these workers, and c) identifying how IS research should adjust to complement new educational initiatives. These questions are provocative because they are rooted in a debate about whether industry investment in modern data technologies requires new workers and skills, new courses and faculty, and a new knowledge base, or whether data science is best understood as a rebranded phenomenon that will be rapidly and effectively absorbed into existing infrastructure.
Recommended Citation
Agarwal, Ritu; Bapna, Ravi; Ghose, Anindya; Shmueli, Galit; Slaughter, Sandra; Tambe, Prasanna; and Goh, Khim Yong, "Does Growing Demand for Data Science Create New Opportunities for Information Systems?" (2014). ICIS 2014 Proceedings. 1.
https://aisel.aisnet.org/icis2014/proceedings/Panels/1
Does Growing Demand for Data Science Create New Opportunities for Information Systems?
260-073, Owen G. Glenn Building
Many employers expect to face a significant shortfall of workers with data science skills in the coming decade. This panel focuses on the opportunities and challenges this poses for the Information Systems community. Specifically, the panel focuses on three key questions at the nexus of data science, skills, and IS: a) characterizing the changes in skill demand from industry in a variety of global economic contexts, b) evaluating the role of IS departments in educating the next generation of these workers, and c) identifying how IS research should adjust to complement new educational initiatives. These questions are provocative because they are rooted in a debate about whether industry investment in modern data technologies requires new workers and skills, new courses and faculty, and a new knowledge base, or whether data science is best understood as a rebranded phenomenon that will be rapidly and effectively absorbed into existing infrastructure.