David Guggenheim

David Guggenheim

Teaching Assistant Professor of Business Administration

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Contact

10 Wohlers Hall

1206 S. Sixth

Champaign, IL 61820

217-244-0880

dgugg2@illinois.edu

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Educational Background

  • PhD, Department of Management, Southern Illinois University, 2016
  • MBA, University of Illinois Springfield at Springfield, 2010
  • B.S., Business Administration/Computer Science, Southern Illinois University, 2009

Positions Held

  • Advisory Board Member, Signum Solutions, 2019 to present
  • Teaching Assistant Professor of Business Administration, Business Administration, University of Illinois at Urbana-Champaign, 2019 to present
  • Assistant Professor of MIS/Data Analytics, Business and Economics, Berea College, 2016-2019

Recent Publications

  • Guggenheim, D., & Vachhani, U. (2021). The Mystery of Feature Scaling is Finally Solved. Towards Data Science, Towards Data Science, NA (NA), NA.  link >
  • Guggenheim, D. (2021). Future-Proof Your Data Partitions. Towards Data Science, Towards Data Science, NA (NA), NA.  link >
  • Setterstrom, A., Pearson, J., & Guggenheim, D. (2018). The Impact of Social Environment on Willingness to Pay for Online Content. Journal of Internet Commerce, 17 (3), 283-309.  link >
  • Guggenheim, D. (2016). The Collision of Indeterminate Environments and Porter's Forces: Uncertainty Fields and Their Impact on Entrepreneurial Alertness. Strategic Change, 25 (3), 239-257.  link >

Teaching Interests

Business data analytics, deep learning, and management information systems.

Research Interests

Predictive and prescriptive machine learning models, data science education, and the digital transformation of organizations.

Current Courses

  • Business Analytics II (BADM 211) Builds on the foundation from the Business Analytics I (BADM 210), synthesizes concepts through hands-on application and project-based learning. Focuses on data acquisition, organization, analysis and visualization in a business setting. Expanding on the use of statistics in generating basic inferences to predictive modeling Identify opportunities for improving business decisions using data, conduct relevant analysis of the gathered and cleaned data, and finally, interpret and present analysis outcomes to decision makers. Using statistical tools and software applications to identify business problems, acquire relevant data, and generate analytic solutions using advanced analytics techniques and tools for generating insights. Introduces the students to analyzing, learning, and prediction using advanced analytics techniques and tools for generating business insights. This course will provide a practical introduction to various techniques regarding clustering, text mining, classification and decision trees, and time series analysis. Finally, the course will introduce advanced and emerging topics in predictive analytics.

  • DataStorytelling&Visualization (BADM 590) Special topics in the general area of business. Topics are selected by the instructor at the beginning of each term.

Contact

10 Wohlers Hall

1206 S. Sixth

Champaign, IL 61820

217-244-0880

dgugg2@illinois.edu

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