Michael Young

Michael Young is the Director of Institutional Research and Decision Support at Kennesaw State University.  He had been the Director of Decision Support at KSU since July 2016. He is responsible for leading the development and implementation of a decision support vision and strategy that improves the quality, timeliness, and relevance of information available to decision makers at KSU. Michael ensures that the Office of Institutional Effectiveness has the required data resources to fulfill its mission of assisting all levels of management in defining issues, selecting research designs, obtaining information, and interpreting results. He is responsible for the development and maintenance of data resources to support the strategic planning and policy-making process at KSU.

Michael was previously the Executive Director of Enterprise Information Management and Institutional Research at Kennesaw State University, where he was responsible for the direction and management of KSU’s SAS-based institutional portfolio and information management solutions. Michael also managed most aspects of KSU’s enterprise data warehouse such as data sourcing, migration, design, and implementation which delivered a data informed culture to KSU. Prior to joining KSU, Michael was the Sr. Director of Institutional Research & Planning at Georgia Institute of Technology, where he was responsible for the development and maintenance of technical and functional data resources to support the strategic planning and policy making processes at Georgia Tech.

Michael received his Bachelor’s in Computer Science from University of Southern Mississippi. He has worked in institutional research since 1998, first at the University of Southern Mississippi, then at Georgia Tech (1999), and (since 2016) at Kennesaw State University. Michael is currently active in the Association of Institutional Research (AIR) and the Southern Association of Institutional Research (SAIR). He has continuing interests in BI strategy, Data Quality, Data Visualization, Predictive Analytics, Metadata and Data Definitions, Machine Learning, and Data Governance.

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