Master of Science in Business Analytics Online
Earning your Master of Science in Business Analytics online from the University of North Carolina Wilmington gives you the skills modern organizations need to remain competitive in a rapidly changing marketplace.
Program Overview
Get to know our 100% online M.S. in Business Analytics program
UNCW's online Master of Science in Business Analytics program prepares you for in-demand career opportunities by teaching you the advanced analysis skills needed to inform business strategies, recommendations and decisions. Taught by experienced faculty who are committed to your success, this rigorous online master’s program gives you a world-class education with an emphasis on real-world application through case studies, simulations and data-intensive projects.
Whether you're seeking professional advancement or to transition to a new career, this Master of Science in Business Analytics program will give you the skills you need to get ahead. Core coursework surveys descriptive, prescriptive and predictive analytics and gives you a solid foundation in application development and programming languages including Python, R, SQL, Cosign Database and Tableau.
You will also learn how to generate statistical reports and create informative data graphics that "tell a story" tailored to your target audience. Choose from a variety of electives—including an optional internship—to hone your focus on specific industries such as marketing, healthcare, supply chain, transportation, sports and cyber security.
This highly affordable, AACSB-accredited online master’s program in business analytics is delivered in a convenient format designed for working professionals. Plus, we don't require a GMAT or GRE, so you can get started right away.
In this online master's in business analytics program, you will:
- Learn tools and techniques to manage analytics on projects in a variety of business environments
- Study model selection, parameter estimation and validation for predictive analytics using algorithms from statistical and machine learning disciplines
- Understand and apply methods of collecting and transforming data into appropriate formats for analysis
- Learn prescriptive analytics modeling techniques for optimization, simulation and decision making
- Gain a foundation in programming, including application development in R and Python and integrating applications into business operations
- Use common statistical forecasting methods—including decision trees, neural networks and stepwise regression—to analyze data, generate statistical reports and create informative data graphics
- Learn tools and techniques to manage analytics on projects in a variety of business environments
- Study model selection, parameter estimation and validation for predictive analytics using algorithms from statistical and machine learning disciplines
- Understand and apply methods of collecting and transforming data into appropriate formats for analysis
- Learn prescriptive analytics modeling techniques for optimization, simulation and decision making
- Gain a foundation in programming, including application development in R and Python and integrating applications into business operations
- Use common statistical forecasting methods—including decision trees, neural networks and stepwise regression—to analyze data, generate statistical reports and create informative data graphics
Career paths for graduates of the online M.S. in Business Analytics program may include:
- Data Scientist
- Management Analyst
- Logisticians
- Market Research Analyst
- Data Scientist
- Management Analyst
- Logisticians
- Market Research Analyst
Also available:
UNCW offers business programs in a variety of in-demand specializations as well as an Executive MBA program. View our business programs.
Accreditation:
UNCW's Cameron School of Business is accredited by AACSB International (AACSB).
Tuition
Take advantage of our affordable online tuition
Designed to be affordable and convenient, our tuition is an outstanding value and far less of a financial investment than many other North Carolina universities. We also offer pay-by-the-course tuition for our online programs. Financial aid is available for those who qualify.
Tuition and fees are subject to change each academic year pending legislative approval. View more information on your cost of attendance.
| Program | Total Tuition & Fees* |
|---|---|
| M.S. – Business Analytics (in-state residents) | $18,865.80 |
| M.S. – Business Analytics (out-of-state residents) | $47,284.20 |
*Estimated tuition and fees are for the full program of study, presuming students are enrolled part-time. Please note the above amounts are estimates of tuition and fees only, based on current tuition rates (2025-2026). Textbooks, class materials, and future tuition and fee increases are not included. Additionally, university tuition is subject to change on an annual basis at the discretion of the UNC System Board of Governors.
Tuition breakdown:
Calendar
Important dates for our students
The M.S. in Business Analytics is delivered 100% online, featuring accelerated 7-week courses and two start dates a year. Choose the start date that is best for you.
| Term | Program Start Date | Application Deadline | Document Deadline | Registration Deadline | Payment Due | Last Class Day |
|---|---|---|---|---|---|---|
| Summer 1 | 5/12/25 | 4/19/25 | 4/19/25 | 5/14/25 | 5/15/25 | 6/29/25 |
| Summer 2 | 6/30/25 | 6/7/25 | 6/7/25 | 7/2/25 | 7/7/25 | 8/17/25 |
| Fall 1 | 8/25/25 | 8/2/25 | 8/2/25 | 8/27/25 | 8/28/25 | 10/12/25 |
| Fall 2 | 10/20/25 | 9/27/25 | 9/27/25 | 10/22/25 | 10/23/25 | 12/7/25 |
Students must register for courses by 5 p.m. (EST) on the registration deadline date.
Students must remit tuition payment by 10 a.m. (EST) on the tuition deadline date.
Now enrolling:
Admissions
Qualifications for our M.S. in Business Analytics online program
To apply for the master’s in business analytics online program, you must hold a bachelor's degree and submit transcripts verifying a minimum cumulative GPA of 3.0.
Admission Requirements:
- No GRE or GMAT
- 3.0 GPA
- Two letters of recommendation
M.S. in Business Analytics Online Admission Requirements:
- An earned bachelor's degree from an accredited college or university
- Minimum 3.0 GPA on undergraduate coursework
- Two letters of recommendation
- Resume with cover letter (serves as statement of interest)
The UNCW Master of Science in Business Analytics requires that applicants complete the following two courses in addition to the core curriculum and electives:
- Statistics - Must be completed PRIOR to starting the MSBA program.
- Applicants who have already completed an undergraduate Statistics course may submit a transcript demonstrating a passing grade of at least a B from an approved college or university.
- Applicants who have not yet completed an undergraduate or graduate-level Statistics course will be required to register for and complete this course prior to full admission to the MSBA program. This requirement may be met through UNCW or at another approved college or university. Please inquire for recommended options to complete this requirement. Applicants are encouraged to proceed with the MSBA application and indicate their plan for completing this requirement prior to the program start date. Qualified applicants will be provisionally admitted to the program, and will be fully admitted pending the completion of a statistics course with a grade of B or better.
- Survey of Business (BUS 500) – May be completed prior to OR during the MSBA program.
- Students with an undergraduate degree other than Business must take BUS 500, which is a broad survey of business topics including Accounting, Finance, Management, Marketing and Operations. This course may be taken concurrently with other MSBA courses during the program.
- Students who have already completed BUS 500 or similar coursework prior to starting the MSBA program may submit a transcript indicating a passing grade of at least a B from an approved college or university.
- Students who have an undergraduate degree in Business will not be required to take this course.
Official transcripts from all colleges/universities are required.
Electronic Method (Preferred):
Password protected transcripts may be sent directly from the institution to [email protected]
Paper Method – Official Transcripts (Envelope Sealed by the Institution):
UNCW Graduate SchoolAttn: Kimberly Goerne Harris
601 South College Rd
Wilmington, NC 28403-5955
Have a question? Call us at 855-306-4734.
Courses
Advance your knowledge in these online Master’s in Business Analytics classes
The M.S. in Business Analytics online curriculum is comprised of 10 courses (30 credit hours), which includes eight core courses (24 credit hours) and two electives (6 credit hours). Students with an undergraduate degree other than business must take an additional course - BUS 500 Survey of Business.
Upon completion of the course, the student will be able to:
- Clearly understanding the significance and applications of descriptive analytical tools
- Identify the nature and usefulness of data and conduct the appropriate descriptive analysis of the data
- Leverage descriptive analytics in supporting informed and strategic business decision-making processes
Upon completion of the course, the student will be able to:
- Understand a scientific approach to solving management problems to help managers make better decisions
- Identify the nature and usefulness of prescriptive analytical tools and conduct the appropriate modeling techniques to solve business problems
- Use prescriptive analytical tools to assist in making business decisions
Upon completion of the course, the student will be able to:
- Recognize fundamental predictive analytics concepts and terminology
- Access and prepare data for use with predictive analytics techniques
- Perform feature transformation and selection
- Select and build appropriate predictive analytics models for quantitative response variables
- Select and build appropriate predictive analytics models for non-quantitative response variables
- Distinguish between supervised and unsupervised learning approaches
- Identify opportunities to apply predictive analytics in a variety of contexts
Upon completion of the course, the student will be able to:
- Evaluate business problems requiring big data analytics
- Choose the best method to use for predictive modeling task at hand
- Implement several machine learning methods and obtain forecasts
- Interpret findings of several data analytics approaches
- Make recommendations on business analytics problems
Upon completion of the course, the student will be able to:
- Assess ability to synthesize and integrate knowledge and skills developed throughout the program
- Create data-driven solutions to address business challenges
- Demonstrate professionalism and effective collaboration as a member of a client-facing project team
Upon completion of the course, the student will be able to:
- Install and navigate through the statistical software package (i.e., R)
- Create scripts within R to reuse code and demonstrate working with various packages including installation and loading within the R environment
- Explain and demonstrate fundamental programming skills such as data types, storage, etc.
- Explain and demonstrate how to import and work with various data in the R environment
- Demonstrate data manipulation including cleaning data, subsetting, etc.
- Demonstrate data visualization using various plots such as scatterplots, boxplots, etc.
- Demonstrate how to manipulate and read data using functions included in the Tidyverse package
- Create output of statistical analyses through the use of RMarkdown
- Perform basic statistical analysis using base R
- Perform plotting and exploratory analysis within the R Package Tidyverse
- Transform data within an existing data set using the dplyr function
- Combine relational tables using the dplyr functions
- Wrangle data using the tidyverse packages readr and tidyr
- Demonstrate how to use other statistical packages/programming languages (e.g., Python) to run similar analyses
Upon completion of the course, the student will be able to:
- Be familiar with database modeling and logical design
- Understand proficiency in developing complex queries to support analytics
Upon completion of the course, the student will be able to:
- Recognize the range of data visualization perspectives from the most abstract to most concrete
- Create effective summaries of data in table form
- Create effective visualizations of numerical data
- Create effective visualizations of categorical data
- Create a visualization to tell a story
- Create an effective visualization with emphasis on design
Students must also choose two of the following courses.
Upon completion of the course, the student will be able to:
- Establish an understanding of concepts and techniques in digital marketing
- Advise a company on managerial problems relating to specific topics in digital marketing
- Develop data analysis and graphing skills
- Apply data analysis methods in Microsoft Excel
- Assess digital marketing campaigns based on data-driven results
Upon completion of the course, the student will be able to:
- Learn critical analytics and decision support techniques specific to health care administration
- Increase efficiency and effectiveness in problem-solving and decision support
- Conduct analyses, simulations, productivity measurements, scheduling, and more
- Discuss the challenge facing healthcare organizations
- Develop skills to leverage advances in both clinical and information technology to improve quality and performance while containing costs
- Locate appropriate data in different commonly used hospital information systems
Upon completion of the course, the student will be able to:
- Investigate the role of data analysis and synthesis in helping a supply chain achieve its objective
- Analyze and improve the effectiveness of supply chain management activities using various data models and performance metrics
- Argue the use of algorithms in transportation problems
- Investigate a real-world supply chain problem in forecasting, inventory, pricing, and transportation and recommend the data needs and solution approached
- Discuss the need for differentiating the supply chain for various scenarios of supply chain drivers
Upon completion of the course, the student will be able to:
- Identify and differentiate between the three areas of analytics
- Explore, clean, visualize, and summarize appropriate data
- Select appropriate analytic models and evaluate model performance
- Identify opportunities to apply analytics in a variety of sports
Upon completion of the course, the student will be able to:
- Recognize different sources of text data and the history, applications, and challenges of quantitative text data analytics
- Recognize and apply text data analytics and natural language processing methods (i.e., for cleaning, organizing, analyzing, visualizing, and describing natural language data)
- Demonstrate problem-solving and critical decision-making skills utilizing text data and appropriate analytical techniques
- Communicate text analysis results clearly to a technical and non-technical audience
**Students taking a full-time course load throughout the program can complete it in as few as 12 months. Consult with your advisor.
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