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M.S. in Business Analytics (Online)

Unlock the power of data and advance your career with the M.S. in Business Analytics degree. Our program provides students, both with and without an analytics background, 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. By choosing our online MSBA, you will be prepared to pursue a career in data analytics, business intelligence, or consulting.

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About Our Online MSBA

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

When you pursue an online Master of Science degree in Business Analytics (MSBA) from 江南体育 State鈥檚 Ambassador Crawford College of Business and Entrepreneurship, you will combine your business skills and analytical expertise. With a master鈥檚 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. 

Online Master's in Business Programs Ranked by U.S. News and World Report

The online MSBA program has  and many courses are Quality Matters certified. Read on for helpful insights about the online MSBA.

Watch a Pre-recorded Informational Webinar  Read the MSBA Blog

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 江南体育 State

 

路 #2: Level Up Your Education - Master of Science in Business Analytics 

What Is a Master鈥檚 in Business Analytics Online Program?

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 江南体育, you are given the flexibility to complete your studies on your own schedule. The online MSBA program鈥檚 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 江南体育 today.

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

Receive Your MSBA Online

江南体育 State鈥檚 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. Best yet, no GRE/GMAT is 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.

Three-Foci Stem Program

Today鈥檚 business world is dependent on information and data management. 江南体育鈥檚 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 江南体育 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 江南体育 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.

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)
  • Na茂ve 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

Probability:

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

Statistics: 

  • Measures of Central Tendencies 
  • Measures of Dispersion
  • Measures of Skewness 
  • Measures of Dependence 
  • Statistical Significance 
  • A/B Testing 
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 

Program Information for M.S. in Business Analytics (Online)

Program Description

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 (Online)

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

Learning Outcomes

Program Learning Outcomes

Graduates of this program will be able to:

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

Coursework

On This Page

Program Requirements

Major Requirements

Major Requirements
BA 54038ANALYTICS IN PRACTICE 3
BA 64018QUANTITATIVE MANAGEMENT MODELING 3
BA 64036BUSINESS ANALYTICS 3
BA 64037ADVANCED D