Faculty

Dr. Rich Huebner

PhD

How I Might Be Able to Assist

Contact me with questions or information about business analytics, data mining, database systems, and other data-related topics. Specific areas of expertise include multivariate statistics (regression, multiple regression, factor analysis) and data mining techniques (clustering, association rules, decision trees, etc). Other areas of expertise include IT strategy, governance, and how top leaders support data mining projects.

Professional Projects or Initiatives of Interest

Development of business analytics curriculum for NECB.
Completion of Coursera courses on Data Science.
Development of a healthcare analytics data warehouse.
Development of analytics bootcamp for University of New Hampshire.

Background

Education

Ph.D. Information Technology, Capella University
M.S., Information Systems, Nova Southeastern University
M.S., Management, Eastern Nazarene College
B.S., Business Administration, Eastern Nazarene College

Courses Taught at CCG

MBA515 Management Information Systems
MBA535 Operations Management
HRM560 Human Resources Metrics & Measurement
GMAT305 Statistics
MBA545 Capstone: Strategic Planning and Decision Making

Professional Experience

New England Quality Care Alliance, Principal Data Architect. Manage a team of developers in implementing a healthcare clinical and financial data warehouse focused around population health management. Also responsible for data governance and project management of application development projects.

Dentsply Implants, Information Systems Manager. Managed a team of application support and database developers focused on improving application used throughout operations and customer service areas. Managed EDI implementation and data warehouse improvement projects. Implemented analytics platform (Tableau Server and Desktop).

Norwich University, Lecturer of Computer Science. Taught classes in Programming (C++ and Python), Database Systems, Software Engineering, Management Information Systems, and Computer Science Capstone. Worked closely with other faculty to improve curriculum in the computing areas.

Publications and Lectures

Huebner, R. (2009). Diversity-based interestingness measures for association rule mining, Proceedings of the 16th Annual Conference of the American Society of Business and Behavioral Sciences, (16)1.

Huebner, R. (2012), A survey of educational data mining research, Research in Higher Education Journal, 18.

Huebner, R. (2012), Barriers to adopting privacy-preserving data mining, Proceedings of the International Conference of the Academic and Business Research Institute (AABRI), Orlando, FL, January 5-7, 2012.