To analyze educational outcomes or evaluate operations, academic institutions need to produce high-quality data. Unfortunately, many institutions do not have accurate, timely, and useful data and information despite investments to manage technology. Furthermore, data management issues in education, including access, quality, and ownership, inhibit the deployment of analytic applications that require high-quality data. A systematic approach to data quality management in academic institutions requires leaders to understand how an organization uses data and ensure that data is of high quality by continuously improving the processes that produce both explicit and tacit data. The purpose of this study was to gain a better understanding of the cultural and technical barriers preventing the implementation of effective data quality management practices in higher education. The results indicated that academic institutions could improve data quality by improving data production processes and developing a quality improvement culture across primary and secondary operations. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com.bibliotheek.ehb.be/en-US/products/dissertations/individuals.shtml.]