Data Science Roles and the Types of Data Science Programs

被引:2
|
作者
Saltz, Jeffrey [1 ]
Armour, Frank [2 ]
Sharda, Ramesh [3 ,4 ]
机构
[1] Syracuse Univ, Syracuse, NY 13244 USA
[2] Amer Univ, Kogod Sch Business, Informat Technol, Washington, DC 20016 USA
[3] Oklahoma State Univ, Res & Grad Programs, Watson Conoco Phillips Chair, Stillwater, OK 74078 USA
[4] Oklahoma State Univ, Management Sci & Informat Syst, Spears Sch Business, Stillwater, OK 74078 USA
关键词
AMCIS; 2017; Data Science; Education; Analytics Education;
D O I
10.17705/1CAIS.04333
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
A growing field, data science (and, by extension, analytics) integrates concepts across a range of domains, such as computer science, information systems, and statistics. While the number of data science programs continues to increase, few discussions have examined how we should define this emerging educational field. With this in mind, during the 23rd Americas Conference on Information Systems (AMCIS'17), a panel discussion explored emerging questions regarding data science and analytics education. This paper reports on that panel discussion, which focused on questions such as what a data science degree is and what a data science program's learning objectives are. The panel also debated if there should be different types of data science-related programs (such as an applied data science program or a business analytics program) and, if so, should there be a common core across the different variations of programs. Information system educators who can gain a better understanding of current trends in data science/analytics education and other information system researchers who are interested in how data science/analytics might impact the broader field of information systems and management education should find interest in this report.
引用
收藏
页码:615 / 624
页数:10
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