The Institute for Advanced Data Analytics (IADA) is a cross-college, interdisciplinary initiative with the College of Engineering, the Fulbright College of Arts and Sciences, and the Sam M. Walton College of Business at the University of Arkansas. The institute is the main resource center and an invested multidisciplinary community on campus for elevating data analytics research, data innovation and practice by helping enterprises meet their needs for talent, tools, education, and solutions in the analytics space. The approach is to focus and foster interdisciplinary expertise in data analytics, data management and data computing across colleges and departments to pursue excellence and discovery in academic and industry solutions using data analytics at the University of Arkansas. 

Its mission is to serve as an operational bridge between the University of Arkansas and enterprises for developing practical, implementable solutions to industry issues and problems. IADA will also serve as a source of continuing education for enterprises that are engaged in Big Data initiatives and which seek to maximize the capabilities of their in-house talent to grow their analytic expertise. IADA is striving to establish partnerships with industry to expand an analytics curricula and educational opportunities (e.g., internships) to ready graduates to make an impact in industry.

The Arkansas High Performance Computing Center (AHPCC) provides expertise, high performance computing hardware, storage, support services, and training to enable computationally-intensive and data-intensive research. AHPCC collaborates and commits resources to IADA in order to enhance the productivity of a growing community of data science researchers, engineers, and scholars through seamless access and integration to computational resources that support open research; and to coordinate and add significant value to the research and discovery effort. The combined resources and knowledge base of AHPCC and IADA provide a significant foundation for the advancement of Data Science and Data Analytics for researchers in all departments and disciplines through the use of interdisciplinary planning efforts and face to face consulting to best understand both requirements and best-case tools and solutions for each project.