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Organizer: Gerald F Davis, U. of Michigan
Organizer: Yong H Kim, U. of Michigan
Organizer: Dennis Ma, The U. of British Columbia
Speaker: Jean-Nicolas Reyt, McGill U.
Speaker: Matthew G. Grimes, Indiana U.
Speaker: Alex Liu, IBM
Speaker: Jennifer Kurkoski, Google
Facilitator: Theodore DeWitt, U. of Michigan
Facilitator: Simone Santoni, Cass Business School, City U. London
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| There is a growing interest among management scholars in incorporating “big data” in their research. This PDW aims to feed this interest and builds on the success of one of the sessions at the OMT café series last year, “"Big Data" Research with MINIMAL Programming Background.” Thus, the primary objective of this PDW is to make big data accessible for management scholars with no prior background in programming. We want people to leave with enough confidence and basic knowledge to be able to figure what big data opportunities exist for their research and how they might pursue those opportunities. In addition, we aim to grow and develop the community of scholars who are interested in big data research but do not have formal training in programming or informatics. We want to help people identify and connect with potential collaborators to conduct scholarly research using big data. |
Social and organizational life are increasingly conducted and tracked online through electronic media, from emails to Twitter feeds to dating sites to GPS phone tracking. The traces these activities leave behind have acquired the (sometimes misleading) title of “big data.” The three main objectives of this PDW will be to: (1) Make big data accessible for scholars with no prior background in programming; (2) Spark connections between scholars with interests in big data; (3) Impart programming skills for using particular methodologies in research.
Pre-registration is required for this workshop. To register online, please visit https://secure.aom.org/PDWReg. The deadline to register online is July 31, 2016. |
| Search Terms: big data | data access | programming |
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