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.

Apply by 5/25/24
Start class 7/1/24 Apply Now
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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.

The U.S. Bureau of Labor Statistics projects a 39% increase in business analytics jobs through 2024. 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 programming and application development. You will also learn how to generate statistical reports and create informative data graphics that "tell a story" appropriately 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 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 and can be completed in as few as 12 months. 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
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

Career paths for graduates of the Master of Science in Business Analytics program may include:

  • Data Scientist
  • Management Analyst
  • Logisticians
  • Market Research Analyst
Career paths for graduates of the Master of Science in Business Analytics program may include:
  • 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.

Total Tuition $17,792.40*
Duration As few as 12 months**
Credit Hours 30

Accreditation:

AACSB Accredited

UNCW's Cameron School of Business is accredited by AACSB International (AACSB).

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Need More Information?

Call 855-306-4734

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Tuition

UNCW’s affordable online tuition

Tuition for the online M.S. in Business Analytics degree program is highly affordable. Financial aid is available for those who qualify.

View additional tuition information+

Program Per Credit Hour Per Course Total Tuition & Fees*
M.S. – Business Analytics (in-state residents) $593.08 $1,779.24 $17,792.40
M.S. – Business Analytics (out-of-state residents) $1,436.19 $4,308.57 $43,085.70

*N.C. resident tuition and fees. Part-time tuition rate. Full-time tuition rate may be lower. Consult with your advisor. Total tuition and fees may vary by student and are subject to change. Learn more.

**Students taking a full-time course load throughout the program can complete it in as few as 12 months. Consult with your advisor.

Tuition breakdown:

Total Tuition $17,792.40*
Per Credit Hour $593.08

UNCW M.S. in Business Analytics Online

Hear our UNCW students talk about the benefits of our accelerated and flexible program and how studying business analytics will improve their professional outlook.

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.

View full calendar  + 

TermProgram Start DateApplication DeadlineDocument DeadlineRegistration DeadlinePayment DueLast Class Day
Summer 15/13/244/13/244/20/245/15/245/16/246/30/24
Summer 27/1/245/25/246/1/247/3/247/8/248/18/24
Fall 18/26/247/27/248/3/248/28/248/29/2410/13/24
Fall 210/21/249/21/249/28/2410/23/2410/24/2412/8/24

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:

Apply Date 5/25/24
Class Starts 7/1/24

Admissions

Qualifications for our M.S. in Business Analytics online program

To apply for the online M.S. in Business Analytics program, you must hold a bachelor's degree and submit transcripts verifying a minimum cumulative GPA of 3.0.

Admission Requirements:

  • Official transcripts
  • Minimum GPA 3.0
  • Two letters or recommendation
View all admission requirements +

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 School
Attn: Kimberly Goerne Harris
601 South College Rd
Wilmington, NC 28403-5955

Have a question? Call us at 855-306-4734.

Please note: The GMAT/GRE is currently waived through the 2024 cycle for all programs.

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.

Expand All
Students in the M.S. Business Analytics online program must take the following courses.
Duration: 7 weeks
Credit Hours: 3
This course covers statistical inference as applied to management decision making and focuses on building linear statistical models and developing skills for implementing statistical analysis in real situations. Applications require the use of statistical analysis programs on the computer.
Duration: 7 weeks
Credit Hours: 3
This course introduces students to the field of prescriptive analytics. Students will learn how to develop and use modeling techniques used extensively in the business world. Both mathematical and spreadsheet skills in MS Excel are utilized for performing optimization, simulation, and decision analysis techniques.
Duration: 7 weeks
Credit Hours: 3
This course explores computer-intensive methods for model selection, parameter estimation, and validation for predictive analytics. The course focuses on techniques and algorithms from the statistical and machine learning disciplines and has a strong programming component. Example topics in this course include ordinary least squares regression, logistic regression, multinomial logistic regression, classification and regression trees, neural networks, support vector machines, naïve Bayes, principal components analysis, cluster analysis, and regularization. Each technique is accompanied with a focus on application and problem-solving.
Duration: 7 weeks
Credit Hours: 3
This course consists of case studies on using statistical methods for prediction in some business settings. The statistical methods used in the cases follow the recent advances in forecasting with big data and include methods such as decision trees and other classification models, neural networks and stepwise regressions. The JMP Pro software, which is available at UNCW, will be utilized in all cases. The course will also include a data intensive project, which will ask students to use the approaches introduced in the cases to forecast the US economy or the stock market
Duration: 7 weeks
Credit Hours: 3
This course requires students to apply theoretical and practical knowledge acquired during the Business Analytics program at a comprehensive capstone project. Students will develop a solution to a real-world problem that will include collecting and cleaning data, building an appropriate model, and using appropriate analytic methods to solve the problem. The course instructor will provide a problem statement and data from either a real-world domain or a close approximation. Students will work individually or in small teams to develop a project plan, appropriate models, and a final recommendation. It may be possible for students to propose their problem statement and data collection, however, all such projects must be instructor approved.
Duration: 7 weeks
Credit Hours: 3
This course introduces the essential general programming concepts and techniques to a data analytics audience with limited or no prior programming experience. Students will learn programming foundations, application development in R and Python, and how to integrate applications with business operations in this class. The course covers hands-on issues in programming for analytics, which includes accessing data, manipulate data objects, analyze data using common statistical methods, generate reproducible statistical reports, and creating informative data graphics. The course introduces software techniques to write functions, debug, and organize and comment code.
Duration: 7 weeks
Credit Hours: 3
This course focuses on the conceptual foundations of relational databases and data management, interpreting database structure for relevant data, data queries and reporting, and searching for data anomalies [sometimes referred to as “data cleansing” of errors and inconsistencies]. Students will become familiar with database modeling and logical design. Proficiency in developing complex queries and report generation is stressed.
Duration: 7 weeks
Credit Hours: 3
This course provides experience in design principles for creating meaningful displays of quantitative and qualitative data to facilitate managerial decision-making. Use of popular and powerful data visualization and dashboarding software tools is emphasized.

Students must also choose two of the following courses.

Duration: 7 weeks
Credit Hours: 3
The focus of this course is to familiarize students with the principles and strategic concepts of marketing analytics, a high growth area that uses computer-based analytical techniques and quantitative modeling to enhance decision-making capabilities of marketing managers. The effective use of marketing analytics offers insights into customer preferences and trends and allows for the detection of patterns, the making of new associations, and the acquisition of a deeper understanding of customers.
Duration: 7 weeks
Credit Hours: 3
This course equips students with health analytics skills to select, prepare, analyze, interpret, evaluate, and present clinical and operational data to improve healthcare outcomes. Theoretical and practical coverage of topics is presented, such as data mining, predictive modeling, association analysis, clustering, and visualization.
Duration: 7 weeks
Credit Hours: 3
This course introduces the application of data analytics in various aspects of supply chain management, including forecasting and inventory management, sales and operations planning, transportation, logistics and distribution, purchasing, and supply chain risk management. Software packages include Excel with Solver and R.
Duration: 7 weeks
Credit Hours: 3
This course explores computer-intensive methods for model selection, parameter estimation, and validation for predictive analytics. The course focuses on techniques and algorithms from the statistical and machine learning disciplines and has a strong programming component. Example topics in this course include ordinary least squares regression, logistic regression, multinomial logistic regression, classification and regression trees, neural networks, support vector machines, naïve Bayes, principal components analysis, cluster analysis, and regularization Each technique is accompanied with a focus on application and problem-solving.
Duration: 7 Weeks weeks
Credit Hours: 3
Prerequisite: Overall GPA of at least 3.0. Academic training and practical experience through work in a private company or public agency. Faculty supervision and evaluation of all study and on-site activity. Students much secure permission of the graduate coordinator.
Duration: 7 weeks
Credit Hours: 3
This course addresses the unstructured data management skills needed for modern data analysis including those salient to big data and real-time data environments. The focus is on unstructured data and its environment. Unstructured data includes web data (blogs, text), user generated content, social media, location-aware data, and digital media among others. Topics covered include extraction methods for real time audio and video data, data capture, cleaning, representation, storage, queries, manipulation, and real-time data management. Also included as they apply to unstructured data environment are data security, governance, and visualization. Students will learn natural language processing and geospatial analytical tools.
Duration: 7 Weeks weeks
Credit Hours: 3
Fundamentals of Data Center technologies and management. Students learn the roles of databases, computing hosts, connectivity, and storage in a data center. The details of storage technologies, storage network protocols and computing architectures are covered. Management and design considerations such as virtualization of resources, metered usage, business continuity, recovery, replication, and security are also discussed. *MIS 527 is not currently being offered but it is intended to be offered in the future.
Duration: 7 weeks
Credit Hours: 3
This course introduces students to a current area of application or a current development of an advanced topic in business analytics. Students will learn how Business Analytics solutions can impact a firm’s ability to create and maintain competitive advantages. Topics may include applications or developments in descriptive, predictive, or prescriptive analytics.
Students with an undergraduate degree other than business must take the following course.
Duration: 7 weeks
Credit Hours: 3
Provides non-business students with a broad overview of the complex and dynamic contemporary world of business. Topics include Accounting, Finance, Management, Marketing and Operations.

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