Business Analytics (M.S.)

Business Analytics (M.S.)

Masters in Business Analytics students studying a problem

Harness the power of data to develop insight into business decisions and organizational questions. The Master of Science in Business Analytics will develop your skills in data analysis and visualization, predicting/forecasting future probabilities and trends, and helping leaders make decisions in resource-constrained environments. With full- and part-time options, it is perfect for those with undergraduate preparation in quantitative oriented business, engineering, mathematics/statistics, economics, or STEM fields. An introductory level of exposure to Calculus is expected. This program is part of the college's Business Analytics Initiative.

Credit Hours: 36   |    Courses: 12  

TUITION RATES for AY 21-22 are expected to be the same as those currently published for AY 20-21.


Why get a master’s degree in business analytics?

Thanks to the vast amounts of data available today, organizations now have greater access to information that can help influence critical business decisions. To make the best use of data, professionals with backgrounds in data analytics, particularly those who have experience helping leaders achieve objectives in resource-constrained environments, are highly sought after. A recent McKinsey Institute report stated that the United States will face a shortage of about 190,000 data scientists and 1.5 million managers and data analysts who can interpret and implement data. Closer to home, demand for business analytics jobs in the New England area is expected to grow up to 22.3% through 2026, according to Hanover Research. With a program that focuses on both the theoretical and practical applications of business analytics, supported by the latest computer programming skills, our graduates can expect to be in high demand for a number of jobs.

Why choose UNH’s M.S. in business analytics program?

Unique focus: The MSBA program will be the first and only accredited business analytics program in New Hampshire. Taught by faculty immersed in big data research, including cybersecurity, students will get exposure to the latest challenges businesses face.STEM designated: With a STEM-designated focus on business analytics, you will graduate from the M.S. in business analytics program and be able to apply for a 24-month OPT STEM Extension to your 12-month Optional Practical Training Program (OPT) period, allowing you to work in the United States for up to 36 months after graduation with no additional visa requirement.
Flexible: Finish your degree in as little as 16 months. Students can choose to follow one of two paths andtake either one or two classes per term. The program takes 2.5 to 3 years for students who choose to take only one course at a time.
Comprehensive: Covers the three main pillars of business analytics, including descriptive, predictive and prescriptive analytics, giving students a full understanding of the discipline.
Convenient: Continue working while you study, thanks to late afternoon/evening in-classroom classes, plus hybrid courses that combine classroom and online components.
AACSB Accredited: Learn at a school that is among only 5% of business schools worldwide to meet the gold standard for the highest quality programs.


  • Analyst and planner (Six Sigma)
  • Business intelligence analyst
  • Data analyst
  • Manager of modeling and analytics
  • Market research analyst
  • Pricing and revenue optimization analyst
  • Project manager
  • Quantitative analyst/modeler


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Curriculum & Requirements

The Master of Science in Business Analytics (MSBA), offered by the Peter T. Paul College of Business and Economics, prepares students for careers related to data analytics and quantitative decision making in modern organizations. Graduates from the MSBA program will be armed with skills in data storing/pre-processing/visualization, in building prediction/forecasting models, and in formulating/solving optimal business decision problems when faced with limited resources. The MSBA program places heavy emphasis on building both the theoretical fundamentals and the practical applications of business analytics supported by relevant and modern programming skills. In addition, the MSBA curriculum is designed to foster teamwork and presentation skills that will help students to seamlessly transition into relevant corporate roles.

The MSBA is a STEM-designated program and consists of 12 courses totaling 36 credit hours of coursework (10 required courses and 2 elective courses from a suggested list). Each course follows an 8-week-long term. The program can be completed in 9 months (taking three courses per term), 12 months (taking two to three courses per term), or 28-33 months (taking one course per term). The MSBA program requires that applicants possess an introductory level of exposure to Calculus and programming. General familiarity with basic concepts from Calculus I, Calculus II (e.g. functions, derivation, and integration), and Linear Algebra (basic matrix operations) as well as prior exposure to at least one programming language (C++, Python, R, Java, SQL, etc.) are highly desirable. Any students without Calculus, Linear Algebra, and programming fundamentals will have access to resources to acquire the relevant background prior to joining the program.

In addition, applicants are required to have a bachelor’s degree and to submit a GMAT or GRE test score from within the last five years. The emphasis will be on the quantitative score for both tests, and waivers will be considered on a case-by-case basis. International students are also required to submit a TOEFL score (waivers will be considered on a case-by-case basis).

The field of Business Analytics has grown rapidly over the last few years due to technological advancements and the ease of access to data for decision making in organizations ranging from small to large. Every firm is interested in hiring and training individuals with analytical capabilities to sustain competitive advantage in the marketplace. A list of examples of careers in business analytics is as follows:

- Business Analytics & Optimization Consultant
- Business Case Modeling Analyst/Consultant
- Business Intelligence Analyst
- Decision Science Analyst
- Analyst & Planner (Six Sigma)
- Internal Quantitative Marketing Strategy Consultant
- Manager of Modeling and Analytics
- Pricing & Revenue Optimization Analyst
- Project Manager/Promotion Response Analytics
- Quantitative Analyst – Asset Allocation
- Quantitative Analyst – Insurance Risk
- Quantitative Marketing Solutions Director & Manager
- Quantitative Modeler
- Quantitative Research Analyst

The MSBA program requires students to take 12 courses (a total of 36 credit hours), from which 10 are required and 2 are electives. A listing of core courses is below.  Part-time students take one course per term; full-time students take two or three courses per term.  

The Foundation
Mathematics for Business Analytics (Online Module) 10
Core Courses
DS 801Business Intelligence3
DS 802Probability and Simulation3
DS 803Fundamentals of Statistical Analysis3
DS 804Exploration and Communication of Data3
DS 805Statistical Learning3
DS 806Optimization Methods I3
DS 807Modeling Unstructured Data3
DS 808Optimization Methods II3
DS 809Time Series Analysis3
DS 810Enterprise Level Analytics (Capstone)3
2 Approved Electives 26
Total Credits36
ADMN 827
Hospitality Operations & Financial Metrics
ADMN 829
Corporate Financial Strategy
ADMN 830
ADMN 834
Private Equity/Venture Capital
ADMN 846
International Financial Management
ADMN 852
Marketing Research
ADMN 863
Marketing Analytics
ADMN 864
New Product Development
ADMN 898
Topics (Digital Marketing)
ADMN 898
Topics (Applied Financial Modeling and Analytics)
ADMN 898
Topics (Big Data in Finance)
ADMN 898
Topics (Project Management)
ADMN 912
Managing Yourself & Leading Others
ADMN 919
Accounting/Financial Reporting, Budgeting, and Analysis
ADMN 926
Leveraging Technology for Competitive Advantage
ADMN 930
Financial Management/Raising and Investing Money
ADMN 940
Managing Operations
ADMN 960
Marketing/Building Customer Value
ADMN 970
Economics of Competition
  • Students will demonstrate knowledge of content areas of business analytics.
  • Students will demonstrate the ability to solve complex problems.
  • Students will demonstrate effective oral communication behaviors.
  • Students will demonstrate effective written communication behaviors.
  • Students will demonstrate ability to cleanse, aggregate, and visualize data.
  • Students will apply statistical inference techniques to business problems.
  • Students will effectively develop and interpret optimization & simulation software output.


Applications must be completed by the following deadlines in order to be reviewed for admission:

  • Fall: June 15th
  • Spring: N/A
  • Summer: N/A
  • Special: Contact Program

Application fee: $65

Campus: Durham

New England Regional: No

Accelerated Masters: Yes (for more details see the accelerated masters information page)

New Hampshire Residents

Students claiming in-state residency must also submit a Proof of Residence form. This form is not required to complete your application, but you will need to submit it after you are offered admission or you will not be able to register for classes.


If you attended UNH after September 1, 1991, and have indicated so on your online application, we will retrieve your transcript internally; this includes UNH-Durham, UNH-Manchester and UNH Non-Degree work. 

If you did not attend UNH, or attended prior to September 1, 1991, then you must request one official transcript be sent directly to our office from the Registrar's Office of each college/university attended. International transcripts must be translated into English. We accept transcripts both electronically and in hard copy:

  • Electronic Transcripts: Please have your institution send the transcript directly to Please note that we can only accept copies sent directly from the institution.
  • Paper Transcripts: Please send hard copies of transcripts to: UNH Graduate School, Thompson Hall- 105 Main Street, Durham, NH 03824. You may request transcripts be sent to us directly from the institution or you may send them yourself as long as they remain sealed in the original university envelope.

Transcripts are required for any school you earned a degree from, attended for at least one year, or attended for 2 or more semesters. Exceptions to this rule may be approved at the discretion of the program you are applying to and the UNH Graduate School Admission’s office.

Letters of Recommendation: 2 Required

Recommendation letters submitted by relatives or friends, as well as letters older than one year, will not be accepted.

Test Scores: GMAT (or GRE) Required

The GMAT (or GRE) is required for admission to the M.S. Business Analytics program. Request official test scores to be sent directly to the Graduate School by the testing service. Our CEEB code is 3918. Test scores more than five years old are not acceptable. Student copies and photocopies of scores are not considered official. To register for an exam, or for more tools to help you prepare for one of the exams, please visit the Graduate Management Admissions Council homepage or the GRE Tests homepage. If you plan on providing GRE test scores in lieu of the GMAT please be sure to email the graduate school (, after you have submitted your application, so they can update your records.

For general information about test scores required for admission into our programs please visit our Test Scores webpage.

Personal Statement/Essay Questions

Prepare a brief but careful statement regarding:

  1. Reasons you wish to do graduate work in this field, including your immediate and long-range objectives.
  2. Your specific research or professional interest and experiences in this field.


A current resume is required with your submitted application.

Important Notes

All applicants are encouraged to contact programs directly to discuss program specific application questions.

Stackable MBA/MSBA degree option: Complete two graduate degrees in two years

Applicants that are applying to the MBA program are now able to apply to the MSBA, to start the MSBA immediately following the MBA. Applicants will fill out distinct applications for each program and transcripts, test scores, and statements of residency will only need to be submitted once. Applicants also pay only one application fee. Please check the box on your MBA application that signifies you are interested in applying to the stackable degree program.  For questions on this new option please reach out to and we will be happy to assist you.


  • International students:  Continuous education for 2 years that satisfies visa requirements
  • STEM OPT opportunities after completing the MSBA
  • All students: Two MBA courses will count as MSBA electives, reducing the MSBA tuition in year two

International Applicants

The University of New Hampshire recommends that international applicants who are living outside of the United States, and are planning on pursuing a research based degree, submit a preapplication form before submitting a full application. Your preapplication request will be carefully reviewed and a decision usually provided within 3 weeks. If your preapplication is approved then it is recommended you then submit a full application. If you are currently living in the United States (on a H1B visa, etc.), or you plan on pursuing a professional master’s degree, then you do not need to submit a preapplication.

Prospective international students are required to submit TOEFL, IELTS, or equivalent examination scores. English Language Exams may be waived if English is your first language. If you wish to request a waiver, then please visit our Test Scores webpage for more information.

Explore Program Details

  • Team Watergrass

Student Participants: Brendan O’Connor, Conor O’Regan, Riley Gardner, Vineeth Appala

 Watergrass offers fundraising, membership, and volunteerism data management services for growing nonprofits concerned with environmental conservation and protection. The students have taken on this project to draw valuable insights from 15+ years of data from ~30 organizations.​ They have accomplished this by developing individual dashboards for each organization, an aggregated dashboard for Watergrass employees, and engineering a predictive model. As a result, each organization that works with Watergrass will be able to investigate specific questions they have pertaining to their donors/fundraising campaigns and Watergrass will be able to provide a high-level overview of the volunteerism landscape.

  • Team EBC

Student Participants: Anthony Morin, Bryson Herring, Carter Mercer 

EB Capital Markets generates its current financial market reports by performing all of its data collection manually and wanted a more interactive client experience. This team evaluated the leading financial APIs and web hosting services to find the best value for EBC where they automated EBC’s data collection via IEXCloud and AlphaVantage and created a proof-of-concept website for clients. EB Capital now has an automatically populated database, and a proof-of-concept website that can be further developed and launched. 

  • Team JNJ

Student Participants: Karen Zhang, Nisha Naugain, Tamilazhagan Ezhil 

J&J’s medical devices section deals with bone replacement surgeries focused on Knees and Hips. Inaccurate prediction of part sizes increases cost in production, inventory and supply chain. This team was assigned with tasks of generating insights from the sample dataset and building machine learning models with higher prediction accuracy. The team accomplished the tasks by building dashboards which showcase quantitative insights on top performers across different variable and identified potential business expansion opportunities. The team also build Machine Learning models which are able to predict the required part size that reduces the overall cost for this department.

  • Team UNH

Student Participant: Jon Olson  

Currently, all the incoming freshmen in the Paul School of Business and Economics are being assigned to their required freshmen classes manually by advisors. This team was tasked with finding a way to assign students more efficiently to predetermined "bundles" of classes. Through a combination of front-end data validation in Excel and an R script that performs the assignment function, the team was able to engineer a process that assigns roughly 90% of the students and eliminates much of the time spent on this tedious task.

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