Nov 21, 2018  
Graduate Catalog 2018-2019 
    
Graduate Catalog 2018-2019

Analytics, M.S.


Program Description

The Master’s of Science in Analytics program at DSU will prepare graduates with the skill set necessary to transform them into analytics and data science professionals. These professionals are needed to solve crucial data-driven business problems and assist with analytics-driven decision making that is needed in the work force as the progression of big data jobs continues to grow.

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. Graduates of these programs may find careers such as analytics professionals, data scientists, data architects, data governance specialists, predictive modelers, business intelligence/analytics developers, data visualization specialists, business analysts, market analysts, financial analysts, supply chain analysts, data analysts, computational scientists, or machine learning software engineers in technical, industrial, business, health care and financial companies of all sizes, as well as in the public sector.

Program Goals

Upon graduation, graduates of the program will:

  • be able to prepare and transfer big data sets into actionable information in an easy-to-understand format to support analytics through the use of advanced data processing tools.
  • be able to select the appropriate analytics techniques and apply advanced analytical tools to solve data analytics problems.
  • be able to demonstrate a good understanding of using information technology and computing languages to implement analytics solutions.
  • be able to assess alternative approaches and infrastructures for implementing big data analytics.
  • be able to manage data analytics projects to ensure delivery of a successful data analytics initiative throughout its life cycle.
  • be able to interpret the results of the analysis.

Program Delivery

Courses in the MSA program may be offered using a variety of instructional delivery methods:

  1. Face-to-face on site in Madison, SD in a traditional classroom setting;
  2. At a distance via Internet, using a combination of both live and/or encoded streaming videos of classes, interactive course web boards, course web sites, and e-mail. All courses are web-enhanced.

Program Completion

The program can be completed on a full or part-time basis, with classes offered in three academic terms, fall, spring, and summer. Time to complete really depends upon the number of credit hours taken per semester and the number of knowledge requirements needed. Full-time students (9 credit hours per semester) can complete the program in four semesters (assuming two knowledge support courses are required). The program must be completed within 5 years of the date the program is started (first course taken).

Admission Requirements Specific to the MSA

Entering students will be required to have a baccalaureate degree from institutions with full regional accreditation for that degree. International students must have an undergraduate (bachelor’s) degree that is the equivalent to a four-year undergraduate degree in the U.S.

  • Minimum undergraduate grade point average of 2.70 on a 4.0 scale (or equivalent on an alternative grading system)
  • Transcripts should show completion of courses in key areas equivalent to:
    • Database design/programming including familiarity with SQL (INFS 760 or STAT 410/510)
    • Understanding of the principles of programming (INFS 605 or equivalent)
    • Understanding of statistical principles (INFS 608 or (STAT 281 and STAT 441/541))

Students who have not had appropriate coursework or acceptable experience to meet the knowledge requirements will be admitted to the program if they meet the other minimum requirements.   However, these students will be required to meet the knowledge requirements by satisfactory completing the specified knowledge support courses as part of their program Plan of Study (POS).

Program Faculty

Jun Liu, Program Coordinator

Dorine Bennett, Omar El-Gayar, Chris Olson, Ronghua Shan, Daniel Talley

Program Requirements


Required courses are to be taken by everyone admitted to the program, they include six core courses (18 credit hours), two required courses (6 credit hours) and two track or elective courses (6 credit hours). Core courses build upon the knowledge support courses or appropriate experience.

Knowledge Courses (9 Credits)


Individuals who do not meet knowledge requirements may be required to take up to 9 additional hours.

Tracks


Assessment/Evaluation Activities


All candidates for graduation must participate in an assessment activity. Students will be provided with specific information to MSA exam during their final semester. The MSA students will complete a comprehensive exam.

The results of the exam are used as one means of evaluating the MSA curriculum by providing information to the faculty who teach the courses.

Course Grades


Course Grades are used as an indirect measure of student attainment of specific program goals and objectives. DSU Program Guidelines require students to maintain a 3.0 GPA in the program, receive no grades below a C, and have no more than 2 grades of a C. If you do not maintain the required “B” average you will be placed on academic probation and given the opportunity to raise your GPA to 3.0 within the next nine credit hours. If you do not raise your GPA to 3.0 you will be suspended from the program. If you receive more than 6 credits of “C” or any grade lower than a “C” you will be suspended from the program. You may appeal the suspension. If students have questions regarding grading, they should review the “Satisfactory Progression” Program Guidelines or speak with their advisor.

MSA Course Rotation


Knowledge Courses


Required only of students who do not meet specific admission knowledge requirements.

Course #

Course Title

FA 18 SP 19 SU 19 FA 19 SP 20 SU 20 FA 20 SP 21 SU 21
INFS 605 Foundations of Programming X     X     X    
INFS 608 Applied Statistics X     X     X    
INFS 760 Enterprise Modeling, & Data Management X   X X   X X   X

MSA Core Courses


Course #

Course Title

FA 18 SP 19 SU 19 FA 19 SP 20 SU 20 FA 20 SP 21 SU 21
INFS 762 Data Warehousing & Data Mining X   X X   X X   X
INFS 772 Programming for Data Analytics   X     X     X  
INFS 774 Big Data Analytics     X     X     X
STAT 600 Statistical Programming* (SDSU)     X     X     X
STAT 601 Modern Applied Statistics I* (SDSU) X     X     X    
STAT 602 Modern Applied Statistics II* (SDSU)   X     X     X  

*Courses taught by SDSU.

Required Courses


Course #

Course Title

FA 18 SP 19 SU 19 FA 19 SP 20 SU 20 FA 20 SP 21 SU 21
INFS 768 Predictive Analytics for Decision Making X     X     X    
INFS 770 Advanced Data Mining Applications   X     X     X  

MSA Tracks


Students must choose one track to complete or the general track which with the consent of advisor a student can choose two elective courses from the INFS, ECON, HIMS and BADM disciplines.

Business (select two classes)


Course #

Course Title

FA 18 SP 19 SU 19 FA 19 SP 20 SU 20 FA 20 SP 21 SU 21
BADM 712 Advanced Business Finance X           X    
BADM 729 Business Analysis for Managerial Decisions       X       X  
ECON 730 Economics for Decision Making   X     X     X  
BADM 775 Strategic Marketing   X     X     X  
BADM 755 Organizational Behavior & Human Resource Mgmt Process     X     X     X

Information Systems (select two classes)


Course #

Course Title

FA 18 SP 19 SU 19 FA 19 SP 20 SU 20 FA 20 SP 21 SU 21
INFS 720 Systems Analysis & Design X X   X X   X   X
INFS 724 Project & Change Management X X   X X   X   X
INFS 764 Information Retrieval X   X X   X X   X
INFS 766 Advanced Database   X     X     X  
INFS 776 Business Intelligence & Visualization     X     X     X

Healthcare Analytics (select two classes)


Course #

Course Title

FA 18 SP 19 SU 19 FA 19 SP 20 SU 20 FA 20 SP 21 SU 21
HIMS 701 Foundations in Healthcare Information X     X     X    
HIMS 742 Healthcare Informatics, Information Systems and Technology   X     X     X  
HIMS 744 Data Analytics in Healthcare     X     X     X
HIMS 746 Health Information Lifecycle Governance X     X     X