Ready yourself for the growing demand.
Surging growth in digital information means businesses are seeking graduates who can transform this raw data into trusted analysis used to develop new business strategies. New jobs for business analytic professionals are expected to exceed 35,000 in the next three years, an increase of more than 15 percent, according a 2017 report supported by IBM and the Business Higher Education Forum.
Learn to manage and leverage big data by pursuing Florida State University’s one-year, full-time Master of Science in Business Analytics (MS-BA). Completed in three semesters on campus, our MS-BA qualifies as a Science, Technology, Engineering or Mathematics (STEM) degree, as defined by the U.S. Department of Education, ensuring students are gaining the priority technical and analytical skills employers seek to remain globally competitive. The STEM designation also allows eligible graduates on student visas to extend their work stay in the United States up to two years longer.
Admission to the Master of Science in Business Analytics program is highly competitive. The decision is based on a portfolio of qualifications, including prior academic performance, work experience, entrance exam scores (such as the GMAT or GRE) and letters of recommendation. The entrance exam is a university requirement that may be waived if an applicant meets certain criteria. For exact criteria and instructions on requesting waivers, see business.fsu.edu/waive.
The GMAT is the preferred exam. If you have not taken the GMAT, you should make plans to take the exam as soon as possible. To register to take the GMAT test, gmat.com.
All applicants must have a bachelor's degree from a regionally accredited institution. Previous coursework in business is not required, but all applicants are expected to have a general knowledge of economics, finance, accounting, statistics, calculus and management principles.
The MS-BA degree program will require students to complete 11 courses (33 credit hours), a combination of 8 core courses (24 credit hours) and 3 elective courses (9 credit hours).
Core courses will include:
- ISM 5136 Data Analytics and Mining for Business
- ISM 5560 Data Management in Business Analytics
- ISM 5565 Foundational Concepts for Business Analytics
- ISM 5566 Forecasting, Revenue Management & Pricing
- ISM 5569 Business Analytics Capstone
- ISM 5644 Programming for Analytics
- QMB 5616 Probabilistic Optimization for Analytics
- QMB 5755 Quantitative Methods in Business Analytics I
Elective course options will include applications of analytical tools in specific business disciplines, such as marketing, human resources, operations, finance or real estate, including:
- ISM 5564 Business Analytics for Competitive Advantage
- MAN 5375 HR Analytics
- MAR 5675 Marketing Analytics
- RMI 5257 Data Analytics in Risk Management and Insurance
*Note: Program requirements are subject to change.
The following items should be submitted through the Florida State Graduate Application portal:
- Applicant Statement
- Current resume/C.V., clearly indicating work experience including dates and positions held, noting full-time or part time employment. Management, business and leadership experience should also be clearly detailed.
- Three (3) letters of recommendation from employers or former college professors that speak specifically to the applicant’s ability to successfully complete the MS-BA program (submitted by the recommenders in the online application).
- Nonrefundable application fee of $30.00 (see University Application or go to fees.fsu.edu)
The following items should be sent to the Admissions Office, PO Box 3062400, 282 Champions Way, Florida State University, Tallahassee, FL 32306-2400:
- One (1) official transcript from all colleges and universities attended (FSU transcripts not necessary for FSU alumni, students)
- Online Florida Residency Declaration Form (see University Application or admissions.fsu.edu/residency)
- Official TOEFL/IELTS score report (required of international applicants whose native language is not English and who have not completed an undergraduate or graduate degree from a U.S. institution or other institution where English is the required language of instruction). The ETS code to send TOEFL scores to Florida State is 5219.
- Official GMAT scores (The code to send GMAT scores to Florida State is PN8K567).
International applicants whose native language is not English and who have not completed an undergraduate or graduate degree in an English-speaking country are required to take either the Test of English as a Foreign Language (TOEFL) or the International English Language Testing System (IELTS) and submit official test results in order to be admitted to The Florida State University. The College of Business requires a minimum TOEFL score of 100 on the internet-based test, or a minimum of 7.0 on the IELTS exam, taken within the past two (2) years.
For more international applicant information, including financial responsibilities, degree equivalency, etc., visit admissions.fsu.edu/international.
WAIVING THE GMAT/GRE
The entrance exam requirement may be waived for outstanding applicants who meet certain criteria.
ESTIMATED PROGRAM COSTS FOR THE 2019-2020 ACADEMIC YEAR
The MS-BA program requires 33 credit hours:
- Florida residents: $479.32 (tuition plus fees) per credit hour. Total estimate program cost is $15,817.56.
- Non-Florida Residents: $1,110.72 (tuition plus fees) per credit hour. Total estimate program cost is $36,653.76.
Costs are subject to change. Fees in table do not include some per-term flat fees for FSUCard and facilities use. For a breakdown of on-campus student fees and their explanations, visit the university’s Tuition Rates page.
Learn more about why our graduate programs are considered A Smart Choice in Value.
Read more about the college’s financial assistance options for graduate students.
You may also visit Florida State's financial aid website for more information on types of financial aid.
ISM 5136 Data Analytics and Mining for Business
This course will provide a managerial overview of the state of art technologies and techniques that are used to discover rich and existing patterns for generating business value, i.e. “business intelligence” for organizations.
ISM 5560 Data Management in Business Analytics
This course will discuss various data-related issues in business analytics and introduce the best practices, underlying principles, and emerging technologies in data management. Specifically, the course will cover 1) foundational data management concepts, 2) best practices in managing big data, and 3) unstructured data management.
ISM 5564 Business Analytics for Competitive Advantage
The course examines the strategic and managerial foundations of business analytics, its use cases and conceptual considerations. Apart from case-led instruction, this course also provides some hands-on experiences with leading-edge software packages, including IBM’s Watson, Tableau, and two textual analytics tools, Semantria and MineMyText.
ISM 5565 Foundational Concepts for Business Analytics
The primary objective of this course is to prepare graduate students in the Business Analytics graduate program with foundational tools and techniques used in subsequent courses. The primary (but not exclusive) focus will be on achieving and understanding of the role of applied probability methods in business analytics.
ISM 5566 Forecasting, Revenue Management & Pricing
This course explores how big data can be used for understanding and analyzing customer demand and behavior. First, the class surveys the canonical uses of data to analyze consumer demand — time-series forecasting. There will be a focus on Exponential Smoothing and ARIMA models. Then, we explore the idea that sales is not the same as demand.
ISM 5569 Business Analytics Capstone
This course is designed for students in Business Analytics to demonstrate that they have achieved the learning goals established by the program regarding descriptive, predictive, and prescriptive data analysis. Upon completion of ISM 5569, students should be able to analyze real world data with consideration of practical concerns. Specifically, this course is to provide students with an advanced level of analytical skills that will enable them to examine business problems by developing models, analyzing alternatives, and recommending solutions using techniques and tools they have learned in previous Business Analytics courses.
ISM 5644 Programming for Analytics
This is an introductory course intended to introduce students to the basics of computer programming for business analytics. The course will place special emphasis on utilizing Python programming language for data science and analytics related tasks.
MAN 5375 HR Analytics
The course focuses on the analysis and application of a company’s HR data to uncover insights that inform HR strategies, process changes, and investments – with the goal of improving organizational performance (i.e., driving business outcomes). Students will learn about theory and research regarding drivers of employee performance, retention, and engagement, as well as the critical HR metrics that are important for business outcomes.
MAR 5675 Marketing Analytics
The practicing marketing scientist must necessarily have a lot of tools in the toolbox. However it is difficult to learn these tools since they have been adopted from a large number of other fields; like psychology, economics and sociology; each with its own notation. This course then will serve as a survey of the Marketing Analytics field, reducing your startup cost to using the techniques needed by the practicing marketing scientist, and to show how marketing analytic techniques feed into the strategic marketing process and business decision-making in general.
QMB 5616 Probabilistic Optimization for Analytics
This course teaches students techniques to address problems in regression, discriminant analysis, principal component analysis, logistic regression, SEM, etc. Students will utilize methods such as calculus and linear algebra.
QMB 5755 Quantitative Methods in Business Analytics I
This course focuses on deterministic methods of perspective analytics
RMI 5257 - Data Analytics in Risk Management and Insurance
In this course we will focus on the use of data and analytical tools in the insurance industry. We will develop a set of tools for analyzing the types of data used by insurers across various functions including loss estimation, loss reserving, underwriting, and claims. Topics will include exploring traditional and new sources of data, legal and ethical considerations, and challenges associated with forecasting and making inferences in the context of risk and uncertainty.
For more information, download our MS-BA brochure.