TY - JOUR
T1 - Data science roles and the types of data science programs
AU - Saltz, Jeffrey
AU - Armour, Frank
AU - Sharda, Ramesh
N1 - Publisher Copyright:
© 2018 by the Association for Information Systems.
PY - 2018
Y1 - 2018
N2 - 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.
AB - 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.
KW - AMCIS 2017
KW - Analytics education
KW - Data science
KW - Education
UR - http://www.scopus.com/inward/record.url?scp=85063981759&partnerID=8YFLogxK
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U2 - 10.17705/1CAIS.04333
DO - 10.17705/1CAIS.04333
M3 - Article
AN - SCOPUS:85063981759
SN - 1529-3181
VL - 43
JO - Communications of the Association for Information Systems
JF - Communications of the Association for Information Systems
IS - 1
M1 - 33
ER -