is a professor at Korea University Business School
. He is an associate editor of the Software Quality Journal and a certified Intro to CMMI-DEV instructor. He served the standardization and Trials of SPICE (ISO/IEC 15504/330xx) a primary editor and co-editor over 20 years. He was a Visiting Scientist at the SEI in 2002 and 2011 and a Visiting Professor at CHEO (Children's Hospital of Eastern Ontario), University of Ottawa in 2010. His recent works focus on (big data) predictive and descriptive analytics with Emcien platform. He received his BS and MS in Industrial Engineering from Korea University and KAIST respectively, and his PhD in MIS from the University of Arizona.
Conference Track: Manage Your data for Peak Performance
The Institute for Operations Research and the Management Sciences released an Analytics Maturity Model (AMM) to assess and improve analytical maturity of organizations in big data era. Since the AMM is a survey based maturity appraisal of 12 questions on Organization, Analytics Capability, and Data & Infrastructures, the model needs best practices for implementation. The objective of this presentation is to provide how the Data Management Maturity (DMM) Model can support the implementation of the AMM. We present a mapping table between the DMM model and the AMM. This study also presents a case study of predictive analytics in big data and its associated DMM process areas.