M.S. in Business Analytics (Online)


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With the emergence of advanced technologies for capturing and analyzing data come a wealth of unparalleled opportunities for those with business analytics expertise. MSBA Ranked #12 best in the nation by Fortune

Kent State's Graduate Business Programs are ranked by U.S. News and World Report.

When you pursue an online Master of Science degree in Business Analytics (MSBA) from Kent State’s Ambassador Crawford College of Business and Entrepreneurship, you will combine your business skills and analytical expertise. With a master’s in business analytics online, you will increase your viability in a competitive market for sought-after analytics professionals who are needed in all industries and organizations. Read on for helpful insights about the online MSBA.

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What Is a Master’s in Business Analytics Online?

An MSBA online program prepares students to enter the field of business analytics. The structure of the program provides students with the definitive knowledge they need to obtain information from a given data set and ultimately make informed business decisions.

Unlike an in-person MSBA, all of the coursework is offered in a completely virtual format, providing greater convenience and flexibility, among other advantages.

What Are the Benefits of an Online MSBA Program?

When pursuing your online business analytics degree at Kent State University, you are given the flexibility to complete your studies on your own schedule. The online MSBA program’s required 30 credit hours can be completed in as few as 12 months, or even over multiple years for those wanting to pace themselves.

Learn more from our informational guide to pursuing your M.S. in Business Analytics online at Kent State University today.

 What Are the Features of Our Master’s in Business Analytics Online Program?

Receive Your MSBA Online

Kent State’s online MSBA program is offered in the fall and spring semesters. Our online business analytics degree offers the same standard of teaching and learning excellence that is delivered on campus, but with the flexibility of online courses. No GRE/GMAT required! 

Plus, our online business analytics degree was designed with the busy working professional in mind. Developed by the same industry-leading faculty who teach in person, our online program prepares you as a leader in the business analytics field.


Today’s business world is dependent on information and data management. Kent State University’s online MSBA program provides graduates with a holistic knowledge of analytics that balances the analytical, technological, and business knowledge needed to collect valuable information from data and make strategic business decisions based on that data.

With a Kent State online business analytics degree, you will gain the technical, analytical, communication, decision-making, and leadership skills you need to be a successful business analyst. The MSBA online curriculum includes integrative capstone analysis projects, as well as an internship option for more professional development through our on-site Career Services Office dedicated to business students.

With our STEM designation, international F-1 students qualify for OPT (Optional Practical Training), granting them the ability to acquire additional and relevant career experience while at Kent State.

What Are the Core Competencies for the Online Business Analytics Degree?

By earning your M.S. in Business Analytics online, you will increase your viability in a competitive market as recruiters regularly seek out those with an MSBA degree.

Data Mining / Machine Learning

Data Mining / Machine Learning

Principles of Machine Learning and Data Modeling

  • Data Structures and Types of Variables
  • Supervised vs. Unsupervised Machine Learning Modeling
  • Data Preparation Techniques
  • Feature Engineering
  • Evaluation of Machine Learning Models
  • Optimizing Machine Learning Models
  • Ensemble Learning
  • Common Mistakes in Modeling

Regression Modeling

  • Concepts and Definitions
  • Performance Metrics
  • Linear Regression
  • Generalized Linear Models (GLM)

Classification Modeling

  • Concepts and Definitions
  • Performance Metrics
  • Logistic Regression
  • k-Nearest Neighbor (k-NN)
  • Naïve Bayes  
  • Decision Trees (applied to Regression as well)
  • Random Forrest (applied to Regression as well)
  • Gradient Boosted Machines (applied to Regression as well)
  • Support Vector Machines (applied to Regression as well)
  • Neural Networks (applied to Regression as well)

Recommendation Systems

  • Concepts and Definitions
  • Performance Metrics
  • Apriori algorithm for association data mining

Time Series Analysis 

  • Concepts and Definitions
  • Performance Metrics
  • Stationarity, causality, and invertibility
  • Autoregressive Integrated Moving Average (ARIMA) 

Graph Analytics

  • Concepts and Definitions
  • Centrality and Connectivity Measures
  • Application to Social Network Analysis

Text Analytics 

  • Concepts and Definitions
  • Feature Extraction
  • Topic Modeling
  • Sentiments Analysis
Programming and Software Tools

Data Mining, Machine Learning and Quantitative Programming: R and Python

Implementation of the following Data Mining/ Machine Learning methods:

  • Linear Regression 

  • Generalized Linear Models  

  • Logistic Regression 

  • Decision Trees 

  • Random Forrest 

  • Gradient Boosted Machines 

  • Support Vector Machines 

  • Neural Networks 

Implementation of the following Quantitative methods: R and Python

  • Linear Programming 

  • Integer Programming 

  • Goal Programming 

  • Simulated Annealing 

  • Network Models 

  • Genetic Algorithms/ Programming 

Data Preparation General Purpose Programming: R and Python

  • Calculating Various Statistics and Math Calculations 
  • Calculating Probability Values 
  • Data Input/ Export 
  • Data Cleansing 
  • Data Wrangling and Data Subsetting 
  • Feature Engineering 
  • Applying summarization and Aggregate functions 

Database: SQL 

  • Principals of Database Design 
  • Using SQL to Create, Update and Delete Tables 
  • Using SQL to Select a subset of Data 
  • Using SQL to Join Tables 
  • Using SQL to perform various Aggregate Functions 

Visualization: R/Tableau/Microsoft Power BI

  • Using R "ggplot" for explanatory analysis and communicating the insights 
  • Using R "Shiny" for interactive visualization and dash boarding 
  • Using Tableau for explanatory analysis and communicating the insights

Software Repository and Development Platforms: Github/Git

  • Creating a new repository 
  • Fork and Push changes to a repository 
  • Clone a public project 
  • Send a pull request/ Merge changes from a pull request 
Applied Probability and Statistics

Applied Probability and Statistics


  • Distributing Functions
  • Normal Distribution 
  • Uncertainty and Confidence Intervals  
  • Conditional Probabilities 
  • Bayesian Probability 
  • Information Entropy 


  • Measures of Central Tendencies 
  • Measures of Dispersion
  • Measures of Skewness 
  • Measures of Dependence 
  • Statistical Significance 
  • A/B Testing 
Databases and Data Processing

Databases and Data Processing 

Relational Databases 

  • Concepts and Definitions 
  • Entity-Relationship Diagrams 
  • Structured Query Language (SQL)
  • Normalization, Transaction management and Concurrency Control 
  • SQL as an Analytical Tool 
  • Intro to NoSQL Databases and Applications 

Big Data Platforms

  • Big Data Paradigms (e.g., MapReduce) 
  • Big Data Platforms (e.g., Hadoop) 
  • Big Data Extraction/Integration 
Quantitative Algorithms


  • Linear Programming 
  • Duality in Linear Programming 
  • Integer Programming
  • Goal Programming 
  • Simulated Annealing 
  • Network Models 
  • Genetic Algorithms/ Programming 
Business Acumen
  • Practical Case Studies Based on Real-World Data from Different Industries 
  • Formulation of Business Problems to Solve Using Analytics Group Projects 
  • Data Collection and Communication of Findings 
  • Operationalizing Analytical Models in Practice 
  • Common Mistakes in Analytical Modeling 

Curriculum Structure of the MSBA Online


Learn More

What Are Kent State’s M.S. in Business Analytics Online Admission Requirements?

Admission to the online MSBA program occurs during the fall and spring semesters and is highly competitive. We strongly recommend applying for our online business analytics degree early, as applications are reviewed on a rolling basis throughout the admission cycle. In addition to the online application form and fee, all applicants must submit the following:

  • Official transcripts from an accredited college or university 
  • Résumé
  • Two letters of recommendation
  • Essay of goals and objectives
  • English score for international applicants (500 TOEFL paper-based, 79 TOEFL IBT, 6.5 IELTS, 110 Duolingo)
  • GMAT/GRE score is not required for this program. 

Please ensure your application materials fully meet the requirements above. We look forward to you joining our master’s in business analytics online program.


Due to its very multi-disciplinary nature, our online MSBA accepts students with different academic backgrounds, including students with business, engineering, computer science, and other science disciplines. Some previous exposure to information/computer systems, applied statistics/math, and business, through coursework and/or work experience, is expected.


msba online






How Much Is the M.S. in Business Analytics Online Tuition?

The tuition information for the master’s in business analytics online program is as follows:

  Ohio Residents Non-Ohio Residents
Below 11 credit hours $549.90 per credit hour $1,024.90 per credit hour
11-18 credit hours $6,036 $11,261.40


  Ohio Residents Non-Ohio Residents
Distance Learning Fee per Credit Hour $15 $15

Learn More | KSU Tuition & Fees

Commonly Asked Questions About Our Online Business Analytics Degree

If you have further questions about Kent State’s MSBA online, our team has prepared answers below for some of the most frequent queries we receive.

What Careers Can I Pursue with an MSBA Online?

Some of the careers that you could pursue with your M.S. in Business Analytics online degree include the following:

  • Chief executive
  • Data scientist
  • Management analyst
  • Statistician
  • Market research analyst
  • Business intelligence analyst

Can I Transfer Credits from Another Graduate Program to an Online MSBA Program?

Yes, typically graduate credits can be transferred from a previous university or a different Kent State graduate program. When transferring your credit, it is important to note that a maximum of 12 hours can be transferred to your online MSBA.

For more information regarding our transfer credit requirements, please visit the transfer of graduate credit academic policies.

Is a Master’s in Business Analytics Online Valued by Employers?

Yes! Completing your M.S. Business Analytics online will give you an advantage in the job market. Candidates with master’s degrees from accredited universities are sought after by employers, particularly those in the business analytics sector.

With that in mind, our faculty at Kent State University encourage potential students to consider the program that is best suited to their schedule and timeframe, either the in-person or online option. No matter which format you choose, our dedicated faculty are ready to equip you with the tools you need to succeed in the business analytics industry.

Online MSBA Faculty

Kent State University’s online MSBA program is taught by full-time faculty with a wealth of analytical, industry experience.


Director, MSBA Program 





Contact Us to Learn More About Our MSBA Online Program

If you would like to know more about our online master’s in business analytics degree or our data analytics courses, be sure to contact us today.


Mason McLeodMason McLeod
Admissions Coordinator








Rouzbeh Razavi, Ph.D. Rouzbeh Razavi, Ph.D.
 Director, MSBA Program






Roberto Chavez Roberto Chavez
 Graduate Programs Director