December 10, 2014 | ATLANTA, Georgia

Teradata University Network Names Three University Teams the Winners of Inaugural Analytics Contest

Showcase for the Data-Driven Workforce of the Future who are Already Solving Business Issues with Big Data and Analytics.
Teradata University Network has named the winners of its inaugural contest on analytics. The winners were selected from a highly competitive field of finalist teams of university undergraduate, graduate and Ph.D. students. Nine teams presented their research at the Teradata 2014 PARTNERS Conference & Expo. The conference was sponsored in part by Teradata Corp. (NYSE: TDC), the big data analytics and marketing applications company.

Developed to provide a showcase for the bright-minded data-driven workforce of the future, the theme for the competition was “Solving Business Issues with Big Data and Analytics.” Students were also exposed to a variety of analytics fields and internship and job opportunities in areas such as integrated marketing management, data integration, big data analytics and operations.
“The original research projects presented by these students were significant and complex, with real value and applicability to business problems. They demonstrated the accelerated learning that takes place when we’re able to teach with the analytics tools and complex data sets that businesses use today,” said Ramesh Sharda, executive director of the board for Teradata University Network and Regents Professor of Management Science and Information Systems in the Spears School of Business at Oklahoma State University.
Contest Winners

Winners were named in three categories: Most Promising Research/Advancing Science; Most Practical/Business Value; and, the People’s Choice Best Presentation. The winning teams are:

Mot Promising Research / Advancing Science Award 
Visualizing Invisible Networks of Knowledge - A Social Network Analysis of Scientific Publications. Presented by Mohammadmahdi (Mahdi) Moqri, with Brent Kitchens - University of Florida.


Most Practical / Business Value Award
Felice’s Roman Style Pizza; A Study in Data Consolidation and Analytics. Presented by
Roderick Dayton, with Madeline Mills, Natalie Perkins and Vasyl Ilchyshyn - Loyola University Chicago.

People’s Choice / Best Presentation Award
Analytics for Autism. Presented by Naznin Larya and Emily Edkins, with Laura Lebeau, Sarah Mucerino and Matt Soroczak - Loyola University Chicago.

Each finalist team made a formal presentation to conference attendees and Teradata University Network faculty board members. They also shared their work with attendees in the exhibition hall. The winner of the Research Award was determined by Teradata University Network faculty board members. The winners of the Most Practical/Business Value Award and the People’s Choice/Best Presentation Award were determined by conference attendees.
Relevant Links

Read Contest Abstracts
Learn more about Teradata University Network
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Mohammadmahdi Moqri (shown) and Brent Kitchens, of University of Florida, won Most Promising Research / Advancing Science Award. Moqri presented results of their social network analysis of scientific publications research to the panel of judges. The analysis revealed the evolution of the field of Management Information Systems, identified core and emerging areas of research, and discovered the research gap between academia and industry.


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Two teams from Loyola University Chicago captured awards. The Most Practical / Business Value Award was awarded for "Felice’s Roman Style Pizza; A Study in Data Consolidation and Analytics," and the People’s Choice / Best Presentation Award was awarded for "Analytics for Autism. Standing in back (L-R): Students Natalie Perkins, Vasyl Ilchyshyn, Matthew Soroczak, Professor of Information Systems Nenad Jukic and students Roderick Dayton and Emily Edkins. Front row: Students Sarah Mucerino, Naznin Larya, Madeline Mills and Laura LeBeau.



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Finalists (L - R , Lanxiazi Liu and Dinesh Nallasasamy and also Asish Nayak, Songyue Chen, not shown) of Oklahoma State University analyzed inpatient Medicare coverage for the Top 100 Diagnosis-related groups or DRGs and the average total payments to predict the average covered costs. This analysis would be beneficial to the Centers for Medicare and Medicaid Services, hospital administrators and patients.


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Analysis of the campus WiFi Network at Georgia Institute of Technology required anonymized raw data to construct utilization predictive models and identify user migration patterns around campus. The "Data Science for Social Good" project team included (L-R), Daniel Sedra, Cornell and Daniel Ulloa, Emory University and, not shown, Richard Zheng, Georgia Institute of Technology.

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