Businesses of all sizes are creating and storing more data than ever before according to IBM—2.5 quintillion bytes per day. Businesses are swimming in data, but often lack the talent and expertise to use it effectively for making decisions, revealing insights, and making predictions. Business analytics experts are changing that. The full-time Master of Science program in business analytics puts students on the leading edge of a burgeoning industry hungry for top notch talent.
Students learn the skills and techniques necessary to turn raw data into actionable insights. Descriptive and diagnostic analytics are just starting points in the program. The skills learned develop students into decision-makers and data scientists adept at using predictive and prescriptive analytics to solve business problems.
The full-time program is located in Iowa City. The plan of study spans 16 months, and includes core courses, internships, and electives.
Learning Outcomes
Graduates will exhibit knowledge and skills relevant to data and its applications in business. They will demonstrate competence in the subareas of:
- descriptive analytics;
- predictive analytics; and
- prescriptive analytics.
Graduates will create and communicate solutions to data-related business problems that impact their organizations and communities. They will:
- approach, address, and solve a loosely defined business problem requiring the use, exploration, and analysis of data; and
- communicate effectively through oral, written, and visual forms.
Graduates will understand and explore ethical and privacy issues related to the use of data in the modern world. They will:
- contemplate ethical and privacy issues arising in their own work; and
- express a working knowledge of the major ethical and privacy issues facing the business-analytics profession, supported with examples from current events.
Graduates will demonstrate the ability to be effective team members in a diverse and complex world. They will:
- engage in effective team processes; and
- lead and support others to achieve collective goals.
The full-time Master of Science program in business analytics requires a minimum of 40 s.h. of graduate credit. Transfer credit may be accepted with approval from the program. A major g.p.a. and a cumulative g.p.a. of at least 2.75 is required in all coursework.
The M.S. with a major in business analytics requires the following coursework.
Code | Title | Hours |
---|---|---|
Core Courses | 19 | |
Experience Course/Project | 3 | |
Electives | 18 | |
Total Hours | 40 |
Core Courses
Code | Title | Hours |
---|---|---|
All of these: | ||
BAIS:6050 | Data Management and Visual Analytics | 3 |
BAIS:6070 | Data Science | 3 |
BAIS:8130 | Business Communication (taken fall and spring semester for 1 s.h. each) | 2 |
BAIS:9100 | Data and Decisions | 3 |
BAIS:9110 | Advanced Analytics | 3 |
BAIS:9400 | Professional Development and Business Acumen (taken fall and spring semester for 1 s.h. each) | 2 |
One of these: | ||
BAIS:6040 | Data Programming in Python | 3 |
BAIS:6060 | Data Programming in R | 3 |
Experience Course/Project
The experience course consists of a group project that solves a semester-long business problem.
Code | Title | Hours |
---|---|---|
This course: | ||
BAIS:6120 | Analytics Experience | 3 |
Electives
Elective coursework allows students to deepen or broaden their skills. Additional electives may be available for credit but must be preapproved.
Code | Title | Hours |
---|---|---|
18 s.h. from these: | ||
BAIS:6040 | Data Programming in Python (if not taken as core course) | 3 |
BAIS:6060 | Data Programming in R (if not taken as core course) | 3 |
BAIS:6100 | Text Analytics | 3 |
BAIS:6105 | Social Analytics | 3 |
BAIS:6110 | Big Data Management and Analytics | 3 |
BAIS:6130 | Applied Optimization | 3 |
BAIS:6140 | Information Visualization | 3 |
BAIS:6150 | Financial Analytics | 3 |
BAIS:6170 | Directed Readings - Graduate Business Analytics | arr. |
BAIS:6180 | Healthcare Analytics | 3 |
BAIS:6190 | Forecasting | 3 |
BAIS:6210 | Data Leadership and Management | 3 |
BAIS:6220 | Business Analytics Certification Workshop | 3 |
BAIS:6230 | People Analytics | 3 |
BAIS:6280 | Cybersecurity | 3 |
BAIS:6400 | Cloud Computing | 3 |
BAIS:9210 | Introduction to Modeling with VBA | 3 |
ACCT:9170 | Advanced Accounting Analytics | 3 |
BIOS:5120/IGPI:5120/STAT:5610 | Regression Modeling and ANOVA in the Health Sciences | 3 |
BIOS:5310/IGPI:5310/STAT:5810 | Research Data Management | 3 |
CS:3210 | Programming Languages and Tools | arr. |
CS:4420 | Artificial Intelligence | 3 |
CS:4470 | Health Data Analytics | 3 |
CS:5110/IGPI:5110 | Introduction to Informatics | 3 |
CS:5430 | Machine Learning | 3 |
ECE:5450/IGPI:5450 | Machine Learning | 3 |
ECE:5490 | Multi-Dimensional Image Analysis Tools and Techniques | 3 |
ECON:4800 | Econometric Analysis | 3 |
ECON:5800 | Econometrics | 3 |
ECON:5805 | Statistics for Economics | 3 |
EPID:5200/IGPI:5220 | Principles of Public Health Informatics | 3 |
FIN:9160 | Quantitative Finance and Deep Learning | 0,3 |
GEOG:3520/IGPI:3520 | GIS for Environmental Studies | 3 |
GEOG:3540/IGPI:3540 | Geographic Visualization | 3 |
GEOG:4150/GHS:4150/IGPI:4150 | Health and Environment: GIS Applications | 3 |
GEOG:4580/IGPI:4581 | Introduction to Geographic Databases | 3 |
GEOG:5540/IGPI:5540 | Geographic Visualization | 3 |
GEOG:5055/IGPI:5055 | Geospatial Programming | 3 |
ISE:3600/CEE:3142/STAT:3620 | Quality Control | 3 |
ISE:4172 | Big Data Analytics | 3 |
ISE:6380 | Deep Learning | 3 |
ISE:6760 | Pattern Recognition for Financial Data | 3 |
ISE:6780 | Financial Engineering and Optimization | 3 |
JMC:3640 | Information and Data Visualization | 3-4 |
MATH:4250 | Introduction to Financial Mathematics | 3 |
ME:4111/CEE:4511 | Scientific Computing and Machine Learning | 3 |
ME:4150 | Artificial Intelligence in Engineering | 3 |
MKTG:9165 | Digital Marketing Analytics | 3 |
MKTG:9310 | Marketing Analytics | 3 |
POLI:3001 | Hawkeye Poll | 3 |
PSQF:6209/EPLS:6209 | Survey Research and Design | 3 |
PSQF:6243/STAT:6513 | Intermediate Statistical Methods | 3 |
PSQF:6246/STAT:6516 | Design of Experiments | 3 |
PSQF:6250 | Computer Packages for Statistical Analysis (not recommended if completed BAIS:6060) | 1-3 |
STAT:4100/IGPI:4100 | Mathematical Statistics I | 3 |
STAT:4101/IGPI:4101 | Mathematical Statistics II | 3 |
STAT:4200/IGPI:4200 | Statistical Methods and Computing | 3 |
STAT:4540/BAIS:4540/IGPI:4540 | Statistical Learning | 3 |
STAT:4560 | Statistics for Risk Modeling I | 3 |
STAT:5100 | Statistical Inference I | 3 |
STAT:5200/IGPI:5199 | Applied Statistics I | 4 |
STAT:5400/IGPI:5400 | Computing in Statistics | 3 |
STAT:6560 | Applied Time Series Analysis | 3 |
STAT:7400/IGPI:7400 | Computer Intensive Statistics | 3 |
URP:6200/PBAF:6200 | Analytic Methods I | 1-3 |
URP:6225/PBAF:6225 | Applied GIS for Planning and Policy Making | 1-3 |
May include 6 s.h. from these: | ||
ENTR:9800 | Entrepreneurship: Advanced Business Planning | 1-3 |
MBA:8140 | Corporate Financial Reporting | 3 |
MBA:8170 | International Economic Environment of the Firm | 3 |
MBA:8180 | Managerial Finance | 3 |
MGMT:3200 | Individuals, Teams, and Organizations | 3 |
MGMT:9150/HMP:6360/PBAF:6278/RELS:6070/SPST:6010/SSW:6247/URP:6278 | Nonprofit Organizational Effectiveness I | 3 |
MGMT:9160/HMP:6365/PBAF:6279/RELS:6075/SPST:6020/SSW:6248/URP:6279 | Nonprofit Organizational Effectiveness II | 3 |
PSQF:5165/EPLS:5165 | Introduction to Program and Project Evaluation | 3 |
M.S./J.D.
The combined Master of Science in business analytics (career subprogram)/Juris Doctor allows students to pursue two degrees simultaneously, earning both more quickly than they would if the degrees were pursued separately. The Department of Business Analytics collaborates with the College of Law to offer the combined program.
Separate application to each degree program is required. Applicants must be admitted to both programs before they may be admitted to the combined program. For more information, see the Juris Doctor, J.D. (College of Law) in the Catalog.
M.S./M.S. in Finance
The combined Master of Science in business analytics (career subprogram)/Master of Science in finance allows students to pursue two degrees simultaneously, earning both more quickly than they would if the degrees were pursued separately. The Department of Business Analytics collaborates with the Department of Finance to offer the combined program.
A single admission application is available for the combined degree program. For more information, see the M.S. in finance in the Catalog.
Applicants must meet the admission requirements of the Graduate College; see the Manual of Rules and Regulations on the Graduate College website.
Applicants must:
- have earned a bachelor's degree from a U.S. college or university, or have earned an equivalent degree from another country;
- submit unofficial transcripts with their application and official transcripts for admission;
- have earned a minimum g.p.a. of at least 3.00 or the international equivalent;
- submit a current résumé that includes information about employment (if applicable), education, extracurricular activities, and community involvement; and
- submit a statement of purpose with a maximum length of 500 words.
Applicants whose first language is not English must submit official test scores to verify English proficiency. They can verify English proficiency by submitting official test scores from the Test of English as a Foreign Language (TOEFL), the International English Language Testing System (IELTS), or the Duolingo English Test (DET). Applicants who use the IELTS or DET are required to take the on-campus English Proficiency Examination.
Application deadlines are as follows.
- Priority deadline: December 15
- International student deadline: March 15
- Domestic student deadline: June 15
Sample Plan of Study
Sample plans represent one way to complete a program of study. Actual course selection and sequence will vary and should be discussed with an academic advisor. For additional sample plans, see MyUI.
Business Analytics (career), M.S.
Academic Career | ||
---|---|---|
Any Semester | Hours | |
40 s.h. of graduate level coursework must be completed; up to 6 s.h. of graduate transfer credits allowed upon approval. More information is included in the General Catalog and on department website. a | ||
Maintain at least a 2.75 cumulative and program GPA. | ||
Hours | 0 | |
First Year | ||
Any Semester | ||
Meet with your Career Management coach and Professional Director. | ||
Attend Career Management Center sessions offered. | ||
Apply to and secure a summer internship or arrange a summer research project. | ||
Hours | 0 | |
Fall | ||
BAIS:6050 | Data Management and Visual Analytics | 3 |
BAIS:6060 or BAIS:6040 |
Data Programming in R or Data Programming in Python |
3 |
BAIS:9100 | Data and Decisions | 3 |
BAIS:9400 | Professional Development and Business Acumen b | 1 |
Elective course c | 3 | |
Arrange for the Career Management Center to review updated resume, then upload to Handshake. | ||
Hours | 13 | |
Spring | ||
BAIS:6070 | Data Science | 3 |
BAIS:9110 | Advanced Analytics | 3 |
BAIS:9400 | Professional Development and Business Acumen b | 1 |
BAIS:8130 | Business Communication d | 1 |
Elective course c | 3 | |
Elective course c | 3 | |
Complete end of semester employment placement survey as requested by Career Management. | ||
Hours | 14 | |
Summer | ||
Internship: complete a summer internship e | ||
Research: complete a summer research project e | ||
Hours | 0 | |
Second Year | ||
Any Semester | ||
Meet with your Career Management coach and Professional Director. | ||
Attend Career Management Center sessions offered. | ||
Hours | 0 | |
Fall | ||
BAIS:6120 | Analytics Experience | 3 |
BAIS:8130 | Business Communication d | 1 |
Elective course c | 3 | |
Elective course c | 3 | |
Elective course c | 3 | |
Complete end of semester employment placement survey as requested by Career Management. | ||
Verify completion of all degree requirements with program administrator. | ||
Apply to and secure post-graduation employment. | ||
Hours | 13 | |
Total Hours | 40 |
- a
- Students must complete specific requirements in the University of Iowa Graduate College after program admission. Refer to the Graduate College website and the Manual of Rules and Regulations for more information.
- b
- BAIS:9400 is taken during both fall and spring of the first year for a total of 2 s.h.
- c
- Choose from a pre-approved elective list or contact academic advisor for consideration and approval of another course.
- d
- BAIS:8130 is taken during both first year spring and second year fall for a total of 2 s.h.
- e
- Choose between a summer internship or summer research project.