Abstract
The United States faces a shortage of data scientists, which will affect many businesses and industries. As the viability and popularity of data warehousing and mining increases, many more qualified analysts will be needed. While programs at the Master’s level can provide technicians who can handle the storage and retrieval of data, the analytical skills needed for true data science requires the training only a doctoral level program can provide. This paper outlines a model for creating an applied doctorate in data science, following similarly styled programs in other technical fields. The program created by following this model could be self-sustaining by leveraging corporate funding of existing employees and sponsorship of new students to supplement more traditional sources of funding.
Recommended Citation
Hosack, Bryan; Power, Daniel; and Sagers, Glen, "Designing Data Science Graduate Programs: A Case for Applied Doctorates in IS" (2014). MWAIS 2014 Proceedings. 16.
https://aisel.aisnet.org/mwais2014/16