M.S. in Business Analytics (In-Person)

Unlock the power of data and advance your career with the M.S. degree in Business Analytics. Our program provides students with the knowledge and skills needed to leverage data analytics to make informed business decisions.

With coursework designed to build proficiency in data analysis, data mining and data visualization, graduates are well-prepared to meet the demands of today's data-driven business environment. With our certificate, you'll be prepared to pursue a career in data analytics, business intelligence or consulting.

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Adam Cooke | crawfordgrad@kent.edu |
330-672-1280
Tamere Massey | tmassey2@kent.edu |
330-672-1225

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In-Person

Combine your business skills and analytical acumen to become a professional with a Master of Science degree in Business Analytics (MSBA).

Admission into the MSBA Program is available in the Fall and Spring - no GRE/GMAT required!

The emergence of advanced technologies for capturing and analyzing data provides unprecedented opportunities for those with business analytics expertise that spans all industries and organizations. By earning a master’s in business analytics, you will increase your viability in a competitive market for sought-after analytics professionals.

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Featured Podcast

We utilized the latest in AI technology to create short (10-15 minute) podcasts about graduate and undergraduate degrees and programs at the Ambassador Crawford College of Business and Entrepreneurship. Listen to the Master of Science in Business Analytics podcast below to learn more about the degree!

#2: Level Up Your Education - M.S. in Business Analytics at Kent State

Ambassador Crawford College · #2: Level Up Your Education - Master of Science in Business Analytics

What Is a Master’s in Business Analytics Program?

An MSBA degree 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.

What Are the Benefits of Completing the MSBA In-Person?

While our online MSBA program provides a number of ways for instructors and students to communicate, the in-person program provides the opportunity to interact frequently with the instructor and fellow students in real time. In-person learning provides opportunities for socialization and network building. A classroom environment can help students focus on learning and presents the ability to receive immediate feedback. Finally, an in-person experience allows you to enjoy Kent State's vibrant atmosphere and take classes in a brand new building - Crawford Hall.

Three-Foci Stem Program

The language of business today is dependent on information and data management. The Kent State University MSBA program provides you with a holistic knowledge of analytics that balances the technologies, analytical and business expertise you need to be able to glean useful information from data and make strategic business decisions.

With a KSU MSBA, you will gain the technical, analytical, communication, decision-making and leadership skills you need to be a successful business analyst. The in-person and 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), which helps them to acquire additional career experience while at Kent State.

What Are the Core Competencies for the Business Analytics Degree?

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

The skills you will acquire as part of our MSBA program can be put to use in everything from small businesses and start-ups to Fortune 100 companies, so you will just need to determine your best fit. Additionally, research from the McKinsey Global Institute and the U.S. Bureau of Labor Statistics shows that talent in the field of data analytics is sorely needed, so you can be confident in knowing that the education you will receive through our data analytics courses will open numerous doors for your career.

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

Program Information for M.S. in Business Analytics (In-Person)

Program Description

Full Description

The Master of Science degree in Business Analytics provides students with a comprehensive knowledge of analytics that balances the technologies, analytical methods and business expertise needed to glean useful information from data to make strategic business decisions. The language of business today is dependent on information and data management, and the emergence of advanced technologies for capturing, preparing and analyzing data provides unprecedented opportunities for those with business analytics expertise that spans all industries and organizations.

Students in the Business Analytics major gain the technical, analytical, communication, decision-making and leadership skills needed to be successful business analysts. The curriculum includes integrative capstone analysis projects, and there is an internship option for additional professional development through the on-site Career Services Office.

Admissions for M.S. in Business Analytics (In-Person)

Admissions

For more information about graduate admissions, visit the graduate admission website. For more information on international admissions, visit the international admission website.

Admission Requirements

Bachelor's degree from an accredited college or university¹
Minimum 3.000 undergraduate GPA on a 4.000-point scale
Official transcript(s)
Résumé
Goal statement
Two letters of recommendation
English language proficiency - all international students must provide proof of English language proficiency (unless they meet specific exceptions to waive) by earning one of the following:²
- Minimum 79 TOEFL iBT score
- Minimum 6.5 IELTS score
- Minimum 58 PTE score
- Minimum 110 DET score

¹: Students entering the program are expected to have the requisite backgrounds in statistics, mathematics, computers and business required for the program. At a minimum, students should have general knowledge of inferential statistics, adequate general business knowledge, basic knowledge of business information systems and technologies and a solid understanding of algebra and general mathematics with some exposure to calculus. Students may fulfill deficiencies in these prerequisites by taking BA 24056, CIS 24053, MATH 11012, MGMT 24163 or equivalents as applicable. The business analytics program director may consider concurrent enrollment according to the strength of the student’s baccalaureate curriculum and preparedness and the courses proposed to be taken concurrently with the prerequisites.
²: International applicants who do not meet the above test scores may be considered for conditional admission.

Application Deadlines

Fall Semester
- Application deadline: March 15 (international student) and June 15 (domestic student)
Spring Semester
- Application deadline: October 1 (international student) and December 1 (domestic student)

Applications submitted after these deadlines will be considered on a space-available basis.

Learning Outcomes

Program Learning Outcomes

Graduates of the program will be able to:

Identify key characteristics of the business problem.
Identify opportunities and constraints of various data analytical frameworks and tools.
Formulate appropriate data analytic techniques to solve the business problem.
Perform necessary data preparation steps (retrieve, clean and manipulate data).
Demonstrate necessary theoretical knowledge and practical skills to implement several data-analytic frameworks using different tools.
Lead and work with teams to frame the business problem.
Convey in writing the outcomes of analytics for stakeholders.
Use visual outcomes of analytics to communicate orally effective messages for stakeholders.

Coursework

On This Page

Program Requirements
Graduation Requirements

Program Requirements

Major Requirements

Course List
Code	Title	Credit Hours
Major Requirements
BA 54038	ANALYTICS IN PRACTICE	3
BA 64018	QUANTITATIVE MANAGEMENT MODELING	3
BA 64036	BUSINESS ANALYTICS	3
BA 64037	ADVANCED DATA MINING AND PREDICTIVE ANALYTICS	3
BA 64060	FUNDAMENTALS OF MACHINE LEARNING	3
BA 64061	ADVANCED MACHINE LEARNING	3
BA 64082	DATABASE MANAGEMENT AND DATABASE ANALYTICS	3
Major Electives, choose from the following:		6
BA 54011	SYSTEMS SIMULATION
BA 54050	DATA VISUALIZATION
BA 54052	TEXT ANALYSIS AND NATURAL LANGUAGE PROCESSING
BA 64028	GLOBAL SUPPLY CHAIN BUSINESS MODELS
BA 64092	INTERNSHIP IN BUSINESS ANALYTICS
BA 64099	CAPSTONE PROJECT IN BUSINESS ANALYTICS
CS 63015	DATA MINING TECHNIQUES
CS 63016	BIG DATA ANALYTICS
ECON 62054	ECONOMETRICS I
EMAT 61010	ENTERPRISE ARCHITECTURE
EMAT 64210	DATA SCIENCE
HI 60411	CLINICAL ANALYTICS
KM 60370	SEMANTIC ANALYSIS METHODS AND TECHNOLOGIES
MGMT 64160	LEADERSHIP AND ORGANIZATIONAL CHANGE
MKTG 65057	MARKETING RESEARCH
Culminating Requirement
BA 64092	INTERNSHIP IN BUSINESS ANALYTICS	3
or BA 64099	CAPSTONE PROJECT IN BUSINESS ANALYTICS
Minimum Total Credit Hours:		30

Graduation Requirements

Graduation Requirements Summary
Minimum Major GPA	Minimum Overall GPA
-	3.000

No more than one-half of a graduate student’s coursework may be taken in 50000-level courses.
Grades below C are not counted toward completion of requirements for the degree.

Minimum 30 credit hours required for the degree is the assumption that students do not have any unmet requirements they need to be successful in the program. The business analytics program coordinator may make further determination of a student’s preparedness for the program and what prerequisite courses, if any, may be required.

Program Delivery

Delivery:
- Fully online
- In person
Location:
- Kent Campus

Accreditation for M.S. in Business Analytics (In-Person)

Accreditation

AACSB International - The Association to Advance Collegiate Schools of Business

Examples of Possible Careers and Salaries for M.S. in Business Analytics (In-Person)

Chief executives

-10.0%

decline

287,900

number of jobs

$185,950

potential earnings

Data scientists and mathematical science occupations, all other

30.9%

much faster than the average

33,200

number of jobs

$98,230

potential earnings

General and operations managers

5.8%

faster than the average

2,486,400

number of jobs

$103,650

potential earnings

Management analysts

10.7%

much faster than the average

876,300

number of jobs

$87,660

potential earnings

Operations research analysts

24.8%

much faster than the average

105,100

number of jobs

$86,200

potential earnings

Statisticians

34.6%

much faster than the average

42,700

number of jobs

$92,270

potential earnings

Notice: Career Information Source

^{* Source of occupation titles and labor data comes from the U.S. Bureau of Labor Statistics' Occupational Outlook Handbook. Data comprises projected percent change in employment over the next 10 years; nation-wide employment numbers; and the yearly median wage at which half of the workers in the occupation earned more than that amount and half earned less.}

Commonly Asked Questions About Our In-Person Business Analytics Degree

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

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

Yes! Completing your M.S. in Business Analytics 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.

What Should I Consider When Choosing an MSBA Degree?

When choosing where you want to complete your MSBA program, it is important to consider the program’s curriculum, faculty expertise, industry connections, reputation, alumni network, career placement opportunities, and more. Additionally, it is vital that the program aligns with your personal and career goals. Kent State is the perfect destination because we have expert faculty who can give you the skills you need to prepare for life after graduation, as well as financial aid opportunities to help you cover costs.

Boost Your Career with Our M.S. in Business Analytics Online Program

Ready to gain the skills and experience you need to advance in your field? Contact the team at Kent State today by either applying to the program or requesting more information.

We look forward to assisting you!

ADAM COOKE

Email | crawfordgrad@kent.edu

Phone | 330-672-1280

TAMERE MASSEY

Email | tmassey2@kent.edu
Phone | 330-672-1225

M.S. in Business Analytics (In-Person)

Contact Us

In-Person

Admission into the MSBA Program is available in the Fall and Spring - no GRE/GMAT required!

Featured Podcast

#2: Level Up Your Education - M.S. in Business Analytics at Kent State

What Is a Master’s in Business Analytics Program?

What Are the Core Competencies for the Business Analytics Degree?

Principles of Machine Learning and Data Modeling

Regression Modeling

Classification Modeling

Recommendation Systems

Time Series Analysis

Graph Analytics

Text Analytics

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

Implementation of the following Data Mining/ Machine Learning methods:

Implementation of the following Quantitative methods: R and Python

Data Preparation General Purpose Programming: R and Python

Database: SQL

Visualization: R/Tableau/Microsoft Power BI

Software Repository and Development Platforms: Github/Git

Probability:

Statistics:

Relational Databases

Big Data Platforms

Program Information for M.S. in Business Analytics (In-Person)

Program Description

Full Description

Admissions

Admission Requirements

Application Deadlines

Learning Outcomes

Program Learning Outcomes

Program Requirements

Major Requirements

Graduation Requirements

Program Delivery

Accreditation

Examples of Possible Careers and Salaries for M.S. in Business Analytics (In-Person)

Commonly Asked Questions About Our In-Person Business Analytics Degree

Boost Your Career with Our M.S. in Business Analytics Online Program

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