SOUTH DAKOTA BOARD OF REGENTS. Committee on Academic and Student Affairs

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1 SOUTH DAKOTA BOARD OF REGENTS Committee on Academic and Student Affairs AGENDA ITEM: III A DATE: December 4-5, 2013 ****************************************************************************** SUBJECT: Intent to Plan: DSU Master of Science in Analytics and SDSU Master of Science in Data Science Dakota State University and South Dakota State University request authorization to develop a proposal for shared master s programs. DSU will house the Master of Science in Analytics which will build from the institution s strengths in information systems, computer science, and information technology. SDSU will house the Master of Science in Data Science which capitalizes on the institution s strength in statistics and computational science. The intention is to meet the growing regional and national needs for a skilled workforce in these two intrinsically related fields by leveraging the inherent synergies between the institutions. Those developing this proposal intend to design the programs in a manner that will allow students to take advantage of the complementary strengths of the courses, programs, and faculty at the two universities. (Continued) ****************************************************************************** RECOMMENDED ACTION Authorize Dakota State University to develop a proposal for a Master of Science in Analytics and South Dakota State University to develop a proposal for a Master of Science on Data Science with the following conditions: 1. The universities will develop these programs collaboratively, establishing a common core of courses. 2. The universities will not request new state resources and the program proposal will identify the sources and amounts of all funds needed to operate the program and the impact of reallocations on existing programs. 3. The university will research existing curricula, consult with experts concerning the curriculum, and provide assurance in the proposal that the program is consistent with current national standards and with the needs of employers. 4. The proposal will define the specific knowledge, skills, and competencies to be acquired through the program and demonstrate how each will be obtained in the curriculum. 5. The proposal will identify the specific measures to be used to determine whether individual students have attained the expected knowledge, skills, and competencies and the consequences for students who do not achieve at the expected levels.

2 Intent to Plan: DSU Master of Science in Analytics and SDSU Master of Science in Data Science December 4-5, 2013 Page 2 of 2 The proposed programs support the Board of Regents Economic Development & Quality of Life strategic goal (Policy 1:21) by promoting growth of research initiatives, expanding graduate education, and contributing to economic development by expanding programs to meet workforce needs. The institutions do not intend to request new state resources. Rather, these programs will be initiated with redirected funds and will be supported by tuition and fee revenues.

3 ATTACHMENT I 3 South Dakota Board of Regents Intent to Plan for a Master of Science in Analytics and a Master of Science in Data Science UNIVERSITY: Dakota State University South Dakota State University DEGREE(S) AND TITLE OF PROGRAM: Master of Science in Analytics (DSU) Master of Science in Data Science (SDSU) INTENDED DATE OF IMPLEMENTATION: Fall 2014 University Approval To the Board and the Executive Director: I certify that I have read this intent to plan, that I believe it to be accurate, and that it has been evaluated and approved as provided by university policy. After approval by the Presidents, a signed copy of the proposal should be transmitted to the Executive Director. Only after Executive Director Review should the proposal be posted on the university web site and the Board staff and the other universities notified of the URL. This intent to plan pertains to the development of two masters degrees that are jointly developed and offered by Dakota State University (DSU) and South Dakota State University (SDSU). DSU will offer the Master of Science in Analytics and will capitalize on DSU s strengths in information systems, computer science, and information technology. SDSU will offer the Master of Science in Data Science and will capitalize on SDSU s strengths in statistics and computational science. As the two fields are intrinsically related, these programs will meet the growing regional and national needs for a skilled workforce by leveraging the established expertise of the respective institutions. 1. What is the general nature of the proposed program? What is the expected demand for graduates in South Dakota? What is the need for the proposed program? Dakota State University and South Dakota State University request permission to develop a joint proposal for a Master of Science degree program in Analytics (MSA) and a Master of Science in Data Science (MSDS). The primary purposes of the proposed programs include: to more effectively recruit and retain high-quality South Dakota students interested in pursuing graduate education and careers in Analytics and Data Science; to better support South Dakota s economic growth in information technology by preparing graduates to work in the key industries of finance and healthcare, along with other industries requiring support of analytics-related technologies;

4 ATTACHMENT I 4 to equip students with the skillset necessary to transform them into Analytics and Data Science professionals, also referred to as data scientists needed to solve crucial datadriven business problems, and assist with analytics-driven decision making; to enhance the pool of students available to assist faculty with Dakota State University s research initiatives, including the Advanced Informatics Research Lab, and the Center for the Advancement of Health Information Technology, and with South Dakota State University s statistical, mathematical and computational regional outreach initiatives to the financial, manufacturing, health care, and other sectors; to provide an expanded selection of elective and support courses for students in DSU s Master of Science degree in Information Systems and to enhance the applicant pool for the Doctor of Science degree in Information Systems; and to provide advanced academic and research opportunities for matriculating, outstanding undergraduate students. Development of these new degree programs is a priority and a strategic focus for both universities. The budget implications are well understood. We put this proposal forward with a strong belief that it will be a successful addition to both institutions. DSU intends to request authorization to deliver the MSA degree program on campus, online, and at the University Center (via DDN) in Sioux Falls. The university does not intend to request any new State resources or any new or increased student fees to implement this program. The program would be supported with internal redirections, external resources and self-support tuition revenue generated by off-campus and distance students. Additional faculty positions, if needed, would be supported with self-support tuition revenue. Dakota State University intends to design a program that will allow students to take advantage of courses offered by South Dakota State University. SDSU intends to request authorization to deliver the MSDS degree program on campus, with at least all core courses be made available online. The university does not intend to request any new state resources or any new or increased student fees to implement this program. The program would be supported with internal redirections, external resources and self-support tuition revenue generated by off-campus and distance students. No additional faculty positions would be needed. South Dakota State University intends to design a program that will allow students to take advantage of courses offered by Dakota State University. Dakota State University and South Dakota State University intend to design the programs in a manner that will allow students to take advantage of courses offered by both universities, taking advantage of the complementary strengths of the courses, programs, and faculty at the two universities. The proposed programs support the Board of Regents Economic Development & Quality of Life strategic goal (Policy 1:21): Promote growth of research initiatives: Graduate students in the proposed program would support DSU s research centers; Expand graduate education;

5 ATTACHMENT I 5 Contribute to economic development by expanding programs to meet workforce needs and offering off-campus and online programs. Workforce Need for Graduates Use of information technology (IT) and statistical analysis continues to grow in business and industry and, along with that growth, comes a need for individuals with advanced training in both fields. Programs proposed here prepare graduates for careers as a data scientist, data architect, data governance specialist, predictive modeler, business intelligence/analytics developer, data visualization specialist, business analyst, market analyst, financial analyst, supply chain analyst, data analyst, algorithms engineer, computational scientist, or machine learning software engineer in technical, industrial, business, healthcare and financial companies of all sizes, as well as in the public sector. South Dakota Demand: Master s level Analytics and Data Science graduates are hired by many companies in South Dakota, as well as companies in the surrounding region and nationally. A partial list of South Dakota companies that currently hire Analytics graduates at both the B.S. and M.S. levels includes: 3M, Avera McKennan Hospital, BrightPlanet, Cabela s, CAPITAL Services, Citibank, Cortrust Bank, Daktronics, EROS Data Center, Fishback Financial Corporation, Great Western Bank, Innovative Systems, Meta Payment Systems, Midland National Life, POET, PREMIER Bankcard, Raven Industries, Reliamax, Sanford Research, Sencore, and Wells Fargo. Employment opportunities also exist in state government with the South Dakota Bureau of Information & Telecommunications, the South Dakota Department of Transportation, the Board of Regents Information Systems and others. To illustrate the demand for these programs, DSU solicited input on employee demand from a variety of regional companies. According to Steve Pederson, CEO of BrightPlanet, the future of the Information Age is Big Data. Currently we face a shortage of IT specialists with sufficient background in analytics. The education potential of the proposed program is critical to the growth and development of BrightPlanet as well as the growth of the IT industry in the state. Our proposed programs will contribute to the workforce development in South Dakota s major industries such as healthcare. Dave Kapaska, Regional President at Avera McKennan Hospital, said, Avera Health has been expanding its electronic health record system throughout its inpatient and outpatient facilities. However, taking the next step to conduct analysis of our data to improve healthcare outcomes is limited by the lack of sufficient IT specialists trained in analytics. The education and training opportunities that will be provided by the proposed program are critical to building health IT workface capacity. Currently we do not have a strong pool of IT specialists with background in analytics and especially with analytics in the healthcare environment. At SDSU, demand for graduates of the MS in Statistics and PhD in Computational Science and Statistics, both closely related to the proposed program, has been strong for several years and continues to grow, as is evidenced by the placement of these graduates in a large number of South Dakota private sector firms, and by the fact that these firms have donated or pledged more than $1,000,000 dollars in support of these programs since 2007

6 ATTACHMENT I 6 Table 1 provides a summary of employment projection for analytics related jobs in South Dakota, from the South Dakota Department of Labor. While analytics-related occupations and titles (e.g., data scientist, data architect, data governance specialist, predictive modeler, business intelligence/analytics developer, etc.) are relatively new and may not be reflected in the current government occupational outlook, this table suggests that there will continue to be strong opportunities for analytics employment within the state. As noted subsequently, reports from organizations such as Gartner, McKinsey, IBM and SAS further confirm the potential of the program. Table 1. South Dakota Department of Labor and Regulation Occupational Estimates and Projections for 2010 & 2020; Selected Occupations Related to Analytics SOC* Code Standard Occupational Classification Title 2010 Base Number of Jobs 2020 Projected Number of jobs Percent Change Computer and Information Systems Managers % Management Analysts % Market Research Analyst % Financial Analyst % Credit Analyst % Computer Systems Analyst % Software developers applications % Statisticians % Source: South Dakota estimates and projections from South Dakota Department of Labor, available at: National demand: Reports by leading research and technology firms predict that Data Analytics, especially Big Data Analytics is poised to usher in the next generation of innovations in productivity and competition and transform national economies. A recent study (Capgemini Inc., 2012) 1 finds that 9 out of 10 business leaders believe data is now the fourth factor of production, as fundamental to business as land, labor and capital. The explosion in digital data combined with new tools for analyzing the data has sparked massive interest in the field of data analytics. Consulting firm Deloitte (Lee and Stewart, 2012) 2 expects over 90 percent of the Fortune 500 companies to initiate Big Data projects by the end of this year. By 2015, 4.4 million IT jobs globally will be created to support big data, generating 1.9 million IT jobs in the United States (Gartner, 2012) 3. According to Peter Sondergaard, senior vice president at Gartner and global head of Research 1 Capgemini Inc. (2012). The Deciding Factor: Big Data & Decision making. Retrieved from 2 Lee, P. and Stewart, D. (2012). Technology, Media and Telecommunications Predictions. Deloitte Touche Tomahatsu Limited. Retrieved from 3 Gartner (2012). Big Data Creates Big Job: 4.4 Million IT Jobs Globally to Support Big Data By Retrieved, from

7 ATTACHMENT I 7 There is not enough talent in the industry. Our public and private education systems are failing us. Data experts will be a scarce, valuable commodity IT leaders will need immediate focus on how their organization develops and attracts the skills required. These jobs will be needed to grow your business. These jobs are the future of the new information economy. Organizations of all sizes are turning to people who are capable of translating this trove of data into predictive insights that lead to business value. In recent years, the title data scientist has been coined to refer to professionals with both IT and statistical training to make discoveries in the world of big data. Data Scientists have been named the sexiest job of the 21 st century (Davenport and Patil, 2012) 4. Moreover, according to the January 2012 Monthly Labor Review published by the US BLS, Computer and mathematical occupations are projected to add 778,300 new jobs between 2010 and 2020, after having added 229,600 new jobs from 2006 to This represents 22.0 percent growth from 2010 to 2020, making the computer and mathematical occupational group the sixth-fastest-growing major occupational group. 5 Demand for data scientists will continue into the foreseeable future. In a survey conducted by EMC 2 (2011), 83% of surveyed business leaders felt that new technology would increase the demand for data scientists and 64% believe that it will outpace the supply of available talent. Although data science is generating new opportunities, our capacity to train new data scientists is not keeping up, and nearly two thirds of respondents foresee a looming shortfall in the number of data scientists over the next five years. New research by the McKinsey Global Institute (2011) 6 forecasts a 50 to 60 percent gap between the supply and demand of people with deep analytical talent. Figure 1 provides a summary of demand for deep analytical positions in a big data world. Projections indicate approximately 140,000 to 190,000 unfilled positions of data analytics experts in the U.S. by 2018 and a shortage of 1.5 million managers and analysts who have the ability to understand and make decisions using big data. Overall, and according to Cain Miller (2012) 7 of the New York Times, universities can hardly turn out data scientists fast enough. Hoping to draw more students toward a career in data analytics, companies such as SAS have been working with several U.S. universities (e.g., North Carolina State University) to develop courses that provide the analytics skills required for today's business environment. DSU solicited input regarding our program from global leaders in data science and analytics such as IBM, SAS, and EMC 2. IBM will collaborate with us and allow no-charge access to software and courseware and participation in the IBM Academic Skills Cloud pilot program. EMC 2 will provide access to curriculum resources through EMC 2 Academic Alliance. SAS also provides access to SAS infrastructure through SAS Academic initiative. Both EMC 2 and SAS will consider providing 4 Davenport, T. and DJ Patil (2012). Data Scientist: The Sexiest Job of the 21st Century. Harvard Business Review. Retrieved from Manyika, J., Chui, M., Brown, B., Bughin, J., Dobbs, R., Roxburgh, C., and Byers, A. (2011). Big data: The next frontier for innovation, competition, and productivity. McKinsey Global Institute. Retrieved from 7 Cain Miller, C. (2013). Data Science: The Numbers of Our Lives. New York Times April 11, Retrieved from

8 ATTACHMENT I 8 internships experiences for students. All of these companies are interested in hiring master slevel graduates, as well as undergraduates. Figure 1. Demand for analytics and data science professionals in the U.S. 2. What is the relationship of the proposed programs to the University s mission as provided in South Dakota statute and Board of Regents Policy? The statutory mission statement for Dakota State University is provided in SDCL : The primary purpose of Dakota State University in Madison in Lake County is to provide instruction in computer management, computer information systems, electronic data processing and other related undergraduate and graduate programs. The secondary purpose is to offer two-year, one-year and short courses for application and operator training in the areas authorized by this section. This authorization includes the preparation of elementary and secondary teachers with emphasis in computer and information processing. Except for degree programs in existence during the academic year, the unique baccalaureate programs authorized for Dakota State University shall not be duplicated by the Board of Regents. The statutory mission statement for South Dakota State University is provided in SDCL : Designated as South Dakota s land-grant university, South Dakota State University, formerly the state college of agriculture and mechanical arts, located at Brookings, in Brookings County, shall be under the control of the Board of Regents and shall provide undergraduate and graduate programs of instruction in the liberal arts and sciences and professional education in agriculture, education, engineering, home economics, nursing and pharmacy, and other courses or programs as the Board of Regents may determine.

9 ATTACHMENT I 9 Board Policy 1:10:5 Dakota State University Mission Statement provides the degrees authorized: A. Undergraduate Programs Associate degree programs are approved in allied health care, business, general studies, and information technology. Baccalaureate programs are approved in allied health care, business, education, information technology, mathematics, and sciences. B. Graduate Programs Master s degree programs are approved in education and information technology. A Doctor of Science degree in Information Systems is approved. The Board has approved six master s programs and one doctoral program for the University: M.S. in Applied Computer Science (approved in 2012) Master of Business Administration (approved in 2010) M.S. in Health Informatics (approved in 2009) D.Sc. in Information Systems (approved in 2005) M.S. in Information Assurance (approved in 2003) M.S.Ed. in Computer Education & Technology (approved in 1999) M.S. in Information Systems (approved in 1999) Board Policy 1:10:2 South Dakota State University Mission Statement provides the degrees authorized: A. Undergraduate Programs Associate degree programs in General Studies and General Agriculture. Baccalaureate programs in the agricultural sciences, aviation, education, engineering and technology, human sciences, humanities and liberal arts, nursing, performing and visual arts, pharmaceutical sciences, physical and biological sciences, and social sciences. B. Graduate Programs Masters degrees in arts and sciences, agricultural and biological sciences, human sciences, education and counseling, engineering and technology, and nursing. Doctor of Philosophy Degrees in Agriculture and Engineering, and the Physical, Biological, and Social Sciences. Professional programs the Doctor of Pharmacy (Pharm D), Nursing (DNP). The Board has approved several master s programs and doctoral programs for the University. Those most pertinent to the proposed program are offered out of the SDSU Department of Mathematics and Statistics. They are: M.S. in Statistics (approved in 2008) Ph.D. in Computational Science and Statistics (approved in 2005) M.S. in Mathematics

10 ATTACHMENT I 10 An M.S. in Analytics and M.S. in Data Science are clearly within the statutory and Board policy mission of both universities. University Priority and Strategic Plan The proposed masters degrees in Analytics and Data Science supports the current DSU and SDSU strategic plans. The DSU Strategic Plan ( includes goals that are directly related to this program request: Expand current information technology leadership through cutting-edge programs. Optimize on-campus student enrollment and enhance program quality by attracting highability students. Advance DSU's emphasis on applied research. Extend DSU's educational outreach through online and alternative-location delivery. The SDSU Strategic Plan ( includes goals that are directly related to this program request, including: Transfer research, scholarship and expertise for the public good. Pursue public/private partnerships that advance innovation, create career opportunities and bolster economic development. Empower faculty, staff and students to collaborate through partnerships within and external to the University, including select partnerships with institutions from abroad. Cultivate aware, engaged and active citizens well prepared to work in local, state, national and global communities. The proposed masters degree programs in Analytics and Data Science supports all of these strategic directions for DSU and SDSU. Alignment and Support for the SD State Science & Technology Plan The proposed masters degree programs in Analytics and Data Science supports the goals for the South Dakota Science and Technology (SD S&T) plan to boost the state s capacity to increase the number of higher paying jobs, to realize earnings for workers and firms, and to enhance the wealth in communities in general. This is accomplished through a multi-pronged approach emphasizing 1) workforce development responding to existing and projected industry needs for analytics professionals as well as enhancing the ability of the state to attract companies to relocate due to the availability of analytics knowledge workers, 2) support for translational research resulting in intellectual property generation, technology transfer to industry and government, and company creation (spin-offs) involving the use of advanced analytics, and 3) service and outreach focus addressing the analytics needs of industry and government through related certificate programs. The proposed masters degree programs in Analytics and Data Science align with the Information Technology sector identified by the SD S&T plan as a target sector with high growth Science, Technology, Engineering & Math (STEM)-oriented potential, and specifically with the analytics and applied statistics sub-sectors. However, the focus on big data analytics of the programs coupled with the significance and prevalence of the need for big data analytics in other sectors makes these programs also relevant to the other sectors identified in the plan, e.g., value-added

11 ATTACHMENT I 11 agriculture and agri-business, sustainable energy, material and advanced manufacturing, and health and nutrition. The proposed programs align with the SD S&T plan along all three strategy areas identified in the plan as integral to the innovation process: growing new value, and talent, and companies. New Value: The proposed programs will provide an interdisciplinary analytics-focused educational opportunity and support for translational research platform for fostering universityindustry partnerships. For example, collaboration with existing industry partners (BrightPlanet, Avera Health, Sanford Health, CAPITAL Card Services, Fishback Financial Corporation, Great Western Bank, and Sanford Research) can inform curriculum design through relevant case studies and real world datasets. Similarly, guest lectures from these partner organizations can provide additional educational value as well as spur new applied research topics for further exploration. Talent: Working with its industry partners, the programs will emphasize the creation of summer internship opportunities in the area of Analytics and Data Science. This will also link faculty and graduate student research with industry needs and by providing graduate assistantships in pursuit of these needs. The objective will be to provide graduate students enrolled in the programs with exposure to real-world problems, to enhance their ability to respond to employer needs, and to ultimately better prepare them for obtaining full time knowledge-based jobs in the state. Companies: The proposed programs will benefit existing companies by training workforce with the expertise needed to best leverage Analytics and Data Science for competitive advantage. Additionally, graduates from the proposed programs will be knowledgeable about novel applications of analytics and data science, which will open new opportunities for professional growth of employees. 3. Are there any related programs in the regental system? If there are related programs, why should the proposed program be added? If there are no related programs within the system, enter None. There are related programs in the regental system: Dakota State University: M.S. in Information Systems M.S. in Applied Computer Science Certificate in Business Analytics South Dakota State University: M.S. in Statistics Justification for the Proposed Programs It is DSU and SDSU s intention to develop a M.S. in Analytics and a M.S. in Data Science with a strong technical and applied emphasis. The proposed programs are fundamentally different from traditional computer science, statistics, and information systems programs which already exist in the SDBOR system. Analytics uses computational and applied statistical methods to

12 ATTACHMENT I 12 resolve business and other real-world problems. A comparison between these existing programs and the proposed programs is provided below. Computer Science A Master s of Science in Computer Science focuses on the science and technology of computing, emphasizing details of computer hardware, architecture, and the design and development of computer software. Graduates of a Computer Science Master's program are typically employed as developers and software engineers in industrial corporations or public service companies. Information Systems A MS in Information Systems program focuses on the integration of information technology with business problems, enabling information systems professionals to understand technological issues as well as business concepts and fundamentals. MIS professionals are business-oriented, technically proficient individuals who are found in every type of industry from health-care and banking to IT industry focusing on ecommerce, Internet marketing, customer relationship management consulting, etc. Statistics A MS in Statistics is designed to provide the graduate with a sound understanding of statistical principle and the ability to develop sophisticated statistical models, preparing graduates to work in business, industry, or government as statisticians or mathematicians. The mathematical prerequisites necessary for admission to and success in an MS in Statistics program are typically greater than those needed for the proposed programs. While these programs produce less depth of statistical knowledge than the MS in Statistics, they produce greater depth of knowledge of data structures, data access, and data management. Thus, graduates of either one of these two types of programs will offer distinct skill sets that complement, rather than compete with, the skill sets of graduates of the other program in the professional world. Analytics and Data Science Data analytics is the science of translating vast amounts of complex data into clear, manageable information in order to make sound decisions. The proposed programs provide a strong foundation in data analytics by bringing together a diverse body of knowledge from applied statistics, statistical learning, machine learning and computer science, consumer behavior, risk management, and decision theory. They combine system development and data management skills provided by the traditional MS in Computer Science or Information Systems and the statistical training of the traditional MS in Statistics with enhanced computational and data analytic training for those planning careers in information intensive industries or research. Applications areas within Analytics include fields such as healthcare, banking, marketing (e.g. market basket analysis, social network and sentiment analysis), supply chain management, and security and fraud detection. As an example, healthcare systems generate vast files of raw data that can be analyzed for answers to important health care questions. Our program stresses a hands-on approach. We will use real-world problems in various domains to prepare students for roles as strategic thought leaders who leverage predictive analysis and predictive modeling to drive business decision making through the examination and manipulation of large datasets. Our program is highly technical and applied. In addition to the

13 ATTACHMENT I 13 science of data and modeling, students will work with SAS, R, and Hadoop/MapReduce - the leading technologies used in the industry of big data. Graduates of the MS in Analytics program will become data scientists and analysts responding to the needs of organizations generating and consuming large amounts of data. The proposed program is intended to meet the big data analytics workforce needs in South Dakota and improve the competitiveness of SD workforce. The programs to be developed by DSU and SDSU will take advantage of faculty expertise at both universities. Graduate programs at DSU include a certificate program in business analytics, Master of Science degrees in Information Systems, Applied Computer Science, Information Assurance, and Health Informatics, and a doctoral program in Information Systems, while graduate programs at SDSU include Master of Science in Statistics, Master of Science in Mathematics and Ph.D. in Computational Science and Statistics. DSU s faculty in information systems has expertise and experience in teaching system development, databases and data warehousing, data mining and predictive modeling, statistical analysis, decision support, and other technologies that form core skill areas of analytics training, while their professors in health informatics and information assurance provide expertise in highly applicable areas including health data analytics, forensic statistics and fraud detection. SDSU s faculty in statistics, mathematics, and the computational sciences have deep expertise across the full spectrum of analytics and applied statistics and mathematics practices pertinent to this program, and years of experience preparing BS, MS, and Ph.D. graduates for analytics positions in South Dakota businesses and industry. Jointly, the DSU and SDSU faculty who will participate in this program have the expertise to address areas that are not the strengths of the other existing programs within the SDBOR system, and the ability to offer a program that will fully prepare students to meet the analytics needs of South Dakota and the region. This differentiation will attract students who are particularly interested in focus areas that will be identified by DSU and SDSU. In recent years, South Dakota has sought to develop and capitalize on research and technology infrastructure at our universities, particularly in instances where commercialization will result. The proposed programs are an essential part of the academic programming infrastructure needed to more fully participate in the high-technology economic development and advancement of our state. This program is intended to help attract and retain high-quality faculty members and students and will strengthen South Dakota s profile as a provider of first-class graduate education in an area important to its future. Dakota State University has been successful in attracting external support for research. Additional graduate students are needed to assist DSU faculty with grant-supported projects. Researchers at the DSU routinely request computing support from information technology/systems-related students and faculty. At DSU, the proposed analytics program will complement the institution s existing information technology-focused graduate programs by providing a strong computational and analytics emphasis. Simply put, students enrolled in this proposed program would become a vital resource for DSU researchers and for state and regional employers. South Dakota State University has been successful in attracting private sector support for its graduate program activities that have been preparing graduate students in analytics since Over that period, firms such as CAPITAL Services, Dacotah Bank, Fishback Financial

14 ATTACHMENT I 14 Corporation, Meta Payment Systems, POET, and Wells Fargo have donated or pledged over $1,000,000 in support of these programs. 4. Are there related programs at public colleges and universities in Minnesota, North Dakota, Montana, and Wyoming? If there are related programs in these states list below under each state and explain why the proposed program is needed in South Dakota. If there are no related programs in a state, enter None for that state. There are no MS in Analytics or MS in Data Science degrees in this region. 5. Are students expected to be new to the university or redirected from other programs? How many majors are expected in the first years of the program? How many graduates are expected? It is anticipated that the majority of students in this program would be new to the University. DSU does not expect that many students from its existing graduate programs would be redirected to this program. However, in the short term, it is likely that a few current students would elect to pursue this degree. Program enrollments of 10 new students a year are anticipated. It is expected that graduates will need 1.5 to 2 years to graduate, depending on their background and time commitment to the program. SDSU expects that most of its students would be new to the program with some being applicants interested in the MS in statistics program who lack the advanced mathematical preparation needed to succeed in that program, but are otherwise qualified for one of the proposed programs. Graduate students would be recruited from Dakota State University s undergraduate programs in computer science and information systems. While DSU bachelor s graduates are successful in finding employment with 100% placement in recent years, the University does expect to recruit some of its graduates to the proposed programs, on-campus, or in Sioux Falls by distance. In particular, the university will market its program to those IT and business related graduates who are already planning to attend graduate school elsewhere. In addition to recruiting its own graduates, DSU intends to market the proposed program to graduates of the other regental universities, to graduates of S.D. private and tribal institutions, and to graduates of out-of-state institutions. At the undergraduate level, the BOR system has a number of computer and business related degree programs. The graduates from these programs would be among those interested in pursuing any of the proposed degree programs. SDSU would recruit students from undergraduate programs in mathematics, engineering, and economics, from SDSU and other universities. 6. Does the university intend to seek authorization to deliver this entire program at any off-campus locations? If yes, enter location(s) and intended start date(s). Does the university intend to seek authorization to deliver this entire program by distance technology? If yes, identify delivery method(s) and intended start date(s).

15 ATTACHMENT I 15 Off-campus locations Sioux Falls, beginning Fall 2014 (via DDN) Distance technology Internet, beginning Fall What are the University s plans for obtaining the resources needed to implement the program? Indicate yes or no in the columns below. Development Start-up Long-term Operation Reallocate existing resources YES YES Apply for external resources NO NO Ask Board to seek new State resources NO NO Ask Board to approve new or increased student fee NO NO DSU and SDSU faculty and administration will cover the needs of the programs through internal staff allocation and adjustments to the course rotation and scheduling process. The programs will be developed to leverage existing faculty and graduate course offerings. Given current faculty expertise, delivery of the degree program should not be a problem. DSU currently has seven faculty members with doctoral degrees in analytics-related areas. An additional ten faculty have terminal degrees in information systems and two faculty members are currently completing doctoral degrees in computer science or software engineering. SDSU has ten faculty with doctoral degrees in analytics-related areas. The infrastructure from other online graduate programs will also extend to this program, which minimizes the need for additional resources. Furthermore, since the program will be offered at a distance, additional resources to support the programs would come from self-support tuition revenue. The proposed degree programs would include a strong computational emphasis. To support this program, we are developing a Hadoop computer cluster that provides high-performance, dataparallel processing for applications utilizing Big Data. In recent years, MapReduce and its Hadoop implementation have gradually become an industry standard in Big Data Analytics and is being increasingly adopted by government and private sectors. Students of the proposed program in Analytics will benefit from access to the Hadoop cluster, gaining valuable experience that will give them a competitive edge in the job market. The proposed programs include courses that will require students to learn how to process and analyze data. We also expose the students to the management side of these resources - setting up a cluster, networking it and understanding the systems administration of it. There are a number of ongoing activities supporting the proposal of the MS degrees in Analytics and Data Science. SAS, IBM and EMC 2 industry partners have committed to provide support for this initiative through their academic alliance programs. Dakota State University has an academic alliance with IBM and VMware, and hosts an extensive virtual computing environment that provides the students of our proposed master s programs with access to selected software at no cost. The computing environment allows access to data mining, analytics, simulation and various software design and programming platforms.

16 ATTACHMENT I Curriculum Example: Provide (as Appendix A) the curriculum of a similar program at another college or university. The Appendix should provide the required and elective courses in the program. Catalog pages or web materials may be used. Identify the college or university and explain why the program may be used as one model when the proposed program is developed. The curriculum for the Master of Science degree program in Analytics, offered at the University of Texas, is provided in Appendix A, while the curriculum for the North Carolina Master of Science in Analytics in provided in Appendix B. These programs will be used as curriculum models when the proposed program is developed. We selected these programs as models since they provide students with a rigorous course of study in major areas of analytics while providing electives that focus on applications of data analytics in different domains. The required courses we plan to offer will be similar to those provided by these programs. We will offer required courses regarding topics from data analytics programming and data management, to predictive modeling and time series analysis. However, we will build upon our current course offerings to provide a full-fledged curriculum in big data analytics.

17 ATTACHMENT I 17 APPENDIX A Master of Science in Business Analytics Information, Risk and Operations Management Department The University of Texas The curriculum for the Master of Science Business Analytics Program is to be completed over approximately 10 months. All students in the program begin coursework in the fall session. Required Courses: MIS 381N: Data Analytics Programming This course is a general introduction to programming and scientific computation using an objectoriented programming language and statistical software. MIS 381N: Optimization and Decision Analysis The course is an introduction to quantitative decision-making. Quantitative decision making adds value to data by using it to build models that can help in the decision making process. We will cover decision analysis, Monte Carlo simulation and mathematical programming including linear programming, non-linear programming and integer programming. The focus will be on formulation and intuition behind the solution techniques rather than the mathematical theory. Formal math skills like calculus, linear algebra, and probability/statistics will be used some but not much. MIS 381N.1: Introduction to Data Management Topics to be covered include: database design, data quality, data transfer, Current definitive DB languages (SQL), and Other DB tools such as NoSQL, Hadoop, Excel, R, SAS, and Visualization. STA 380: Introduction to Business Data Analytics In this course, we will examine how data analysis technologies can be used to improve decisionmaking. We will study the fundamental principles and techniques of data mining, with realworld examples and cases to place data-mining techniques in context, to develop data-analytic thinking, and to illustrate that proper application is as much an art as it is a science. In addition, we will work "hands-on" with data mining software. MIS 382N.9: Advanced Data Analytics I: Predictive Modeling In this course we will study a variety of advanced techniques for predictive analytics. Particular emphasis will be given to approaches that are scalable to very large data sets and/or those that are relatively robust when faced with a large number of predictors, and algorithms for heterogeneous or streaming data. Many of these capabilities are essential for handing BIG DATA.

18 ATTACHMENT I 18 STA : Advanced Data Analytics II: Unsupervised Learning and Time Series This course is about unsupervised statistical machine learning for all kinds of data and about supervised learning for time-sequenced data. Real data sets will be used throughout the course for motivation, illustration of techniques, and practice. SAS software will be used. No previous experience with SAS will be assumed, but it would be helpful to have had some experience writing simple software code in some programming language. MIS 382N.11: Business Intelligence Capstone Brings together foundations of business analytics related to database management, data analysis techniques and business decision making to solve a business problem of a real-world client. Elective Courses EE 380L: Advanced Data Mining and Web Analytics MKT 382: Marketing Analytics I (offered Spring 2014) RM 392.5: Computational Finance LIN 386M/CS 395T: Data-intensive Computing for Text Analysis MKT : Marketing Analytics II (offered Spring 2014) OM 386: Pricing and Revenue Optimization MIS 382N.12: Social Media Analytics (offered Spring 2014) OM : Supply Chain Analytics (offered Summer 2014)

19 ATTACHMENT I 19 APPENDIX B Master of Science in Analytics Institute for Advanced Analytics North Carolina State University The curriculum for the Master of Science in Analytics Program is to be completed over approximately 10 months. All students in the program begin coursework in the summer session. Required Courses (All courses are required. There are no electives). SUMMER SEMESTER AA 500 Analytics Tools and Techniques FALL SEMESTER AA 504 Analytics Practicum I Orientation and Introduction Data Privacy and Security Data Querying and Reporting Legal Issues Data Access and Management Data Visualization Data Cleaning Geospatial Data Statistical Programming Project Management Data Mining Overview Teamwork and Conflict Resolution Geospatial Data Analytics Leadership/Followership Relational Databases and Data Warehouses Consulting Skills Statistical Analysis of Databases Problem-Solving Linear Algebra Overview Communication Skills Data Visualization Technical Writing Presentation Skills Teamwork Skills SPRING SEMESTER Problem Solving Skills AA 503 : Analytics Methods and Applications AA 501 : Analytics Foundations II Exploratory Data Analysis Advanced Modeling Linear Regression Big Data Multiple Linear Regression Text Mining Regression Diagnostics Advanced Modeling Logistic Regression Risk and Financial Analytics ANOVA Marketing Science: Web Analytics Analysis of Tables Marketing Science: Customer Analytics Statistics Assessments Advanced Exploratory and Outlier Analysis Written and Computer Application Special Topics FALL SEMESTER AA 502 : Analytics Methods and Applications I Time Series and Forecasting Linear Algebra Data Mining AA 505 Analytics Practicum II Data Security Project Management Data Visualization Teamwork Skills Visual Communication of Data Presentation Skills

20 ATTACHMENT I 20 Survival Analysis Logistic Regression Models Linear Programming/Simulation Nonlinear Programming/Optimization Advanced Modeling Databases and Programming Marketing Science: Customer Analytics Technical Writing