Collaborating with faculty, students and corporate partners, the Krenicki Center for Business Analytics & Machine Learning enhances research and dissemination of state-of-the-art information technologies and analytical techniques to utilize the vast amounts of data available today in order to deliver actionable insights into business decision making.
Purdue University alumnus John Krenicki Jr. and his wife, Donna, have given a $5 million gift to a business analytics center in the Krannert School of Management. As a result, the Business and Information Analytics Center will now be known as the John and Donna Krenicki Center for Business Analytics and Machine Learning, pending Board of Trustees approval.
Private and public enterprises increasingly realize the value of data as a strategic asset. Organizations with significant investments in acquiring, managing and analyzing data to enhance decision-making are competitively advantaged over peers that may not devote sufficient attention and resources to these activities. To help organizations and individuals excel in the data-driven business world, Purdue University’s Krannert School of Management is pioneering a bold, comprehensive initiative - the Krenicki Center for Business Analytics & Machine Learning.All areas of Krannert have a strong interest in data-centric work and will benefit from the cutting-edge research and experiential learning projects for both undergraduate and graduate students that the Krenicki Center will foster, making Purdue a leader in STEM-based business education and research.
The Krenicki Center differs from many existing centers/efforts in this domain because it places equal emphasis on technologies and techniques, the twin requirements for success in the emerging world of Big Data, according to a recent McKinsey & Company report. This center will encompass data-analytics-oriented initiatives spanning all areas of business and economics, cooperate and coordinate with other data-intensive efforts at Purdue and collect and house data from public proprietary, simulated and experimental sources for exploration, modeling and prediction.