Master of Science in Applied Digital Technology - Business Analytics Online
Ready yourself for a broad range of career opportunities in business and tech with a Master of Science in Applied Digital Technology with a Concentration in Business Analytics from Arkansas State University.
Program Overview
Review the online M.S. in Applied Digital Technology – Business Analytics program
In this 100% online program, you will examine how information systems aid managers in decision making, learn the principles of project management, and study current topics pertinent to management and society. Explore the tools that use data to make informed management decisions and perform an in-depth study of data mining — focusing on the knowledge discovery process and how it is harnessed for decision support systems (DSS). Gain experience in a hands-on capstone course where student teams develop and present strategic plans for public, private, profit and not-for-profit organizations.
Designed for flexibility, this online program can be customized with a blend of business and technology electives to meet your personal and professional goals.
In this 100% online M.S. in Applied Digital Technology – Business Analytics, you will learn how to:
- Effectively quantify and communicate the business requirements for technology-related projects
- Assess and understand the impacts of technology decisions on management and business operations
- Apply project management concepts to manage a technologically related project from concept to delivery
- Tailor a portion of your degree with a second area of emphasis or a blend of business and technology related elective courses
- Understand data mining and its role in determining requirements for data modeling
- Utilize data mining and data tools for effective business decision-making
- Effectively quantify and communicate the business requirements for technology-related projects
- Assess and understand the impacts of technology decisions on management and business operations
- Apply project management concepts to manage a technologically related project from concept to delivery
- Tailor a portion of your degree with a second area of emphasis or a blend of business and technology related elective courses
- Understand data mining and its role in determining requirements for data modeling
- Utilize data mining and data tools for effective business decision-making
As a graduate of the M.S. in Applied Digital Technology – Business Analytics program, you will be prepared for advancement into roles such as:
- Project Manager
- Director of Process Improvement
- Implementation Analyst
- Data Analyst
- Data Manager
- Business Analyst
- Analytics Manager
- Project Manager
- Director of Process Improvement
- Implementation Analyst
- Data Analyst
- Data Manager
- Business Analyst
- Analytics Manager
Also available:
A-State offers a variety of graduate programs in a convenient online format. Explore our full range of online graduate programs.
Tuition
Earn your degree affordably with our low-cost tuition
Our online M.S. in Applied Digital Technology – Business Analytics program offers the same affordable tuition to all U.S. residents. All fees are included. Tuition may be subject to change on a yearly basis.
Tuition breakdown:
Calendar
Follow these dates to apply, enroll and start classes
Ideal for working professionals, Arkansas State online programs are delivered in an accelerated format with multiple start dates each year.
Please note Summer 1 and Summer 2 terms are 5 weeks in duration for this program.
| Term | Program Start Date | Application Deadline | Document Deadline | Registration Deadline | Payment Due | Last Class Day |
|---|---|---|---|---|---|---|
| Spring 1 | 1/12/26 | 12/15/25 | 12/15/25 | 1/8/26 | 1/9/26 | 2/27/26 |
| Spring 2 | 3/9/26 | 2/23/26 | 2/23/26 | 3/5/26 | 3/6/26 | 5/1/26 |
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Admissions
Learn about our streamlined admission process
A-State Online offers a streamlined admission process to help you get started quickly and easily. To be admitted to the M.S. in Applied Digital Technology – Business Analytics online program, you must have a bachelor's degree from an accredited institution.
Admission Requirements:
- Online application
- Bachelor's degree
- Cumulative GPA 2.5
- Bachelor’s degree from an accredited university with at least a 2.5 cumulative GPA or a 2.75 in the last 60 hours (undergraduate, graduate or combination thereof) or graduate or post-baccalaureate professional degree from a regionally accredited (U.S.) institution
- If you have lower than a 2.5 cumulative GPA and less than a 2.75 in the last 60 hours, you may still apply for consideration for admittance by including a statement of purpose as part of the application. Please contact an Enrollment Services representative at 866-621-8096 for more information.
Note: If you are admitted and have less than a 2.75 cumulative GPA and less than a 3.0 GPA in the last 60 hours, you must make a grade of B or better in each course during the first 6 hours of graduate work at Arkansas State University. Additionally, you will only be allowed to enroll in one course (or 3 graduate hours) per 7-week session for the first two sessions.
Application submission requirements
- Complete online application
- Submit a nonrefundable $30 fee.
- Have official transcript(s) sent from the registrar of the college/university attended. Official transcripts are sealed transcripts sent from the granting institution.
Submit all documents to:
A-State OnlineP.O. Box 2520
State University, AR 72467
Fax: 870-972-3548
Email: [email protected]
Courses
Take a closer look at the online M.S. in Applied Digital Technology – Business Analytics courses
To graduate from the M.S. in Applied Digital Technology – Business Analytics online program, you must complete a total of 33 credit hours. Required coursework includes four core courses (for a total of 12 credit hours), four concentration courses (for a total of 12 credit hours) and three elective courses (for a total of nine credit hours).
Visit the Course Registration page to view the course schedule for this degree.
What are management information systems?
Management information systems use technology infrastructure to support organizational operations and strategic objectives across operational, tactical, and strategic levels. They include database architectures, enterprise resource planning, business intelligence tools, and IT governance frameworks. These systems align technology investments with business goals.
This course examines how organizations utilize information systems to support operations, facilitate decision-making, and achieve a competitive advantage. You will analyze information needs across different organizational levels—from operational systems that handle daily transactions in finance, marketing, and production to executive information systems that support strategic planning.
Upon completion, students will be able to:
Deliver effective oral presentations
Lead and productively participate in group situations
Apply quantitative and qualitative knowledge to solve problems and make decisions
Student progress will be assessed through case preparation, discussion, presentations, examinations, and debriefing write-ups.
What is data mining?
Data mining discovers patterns and insights in large datasets through the knowledge discovery process. It uses algorithms for classification, clustering, association rules, and predictive analytics. This technique extracts valuable knowledge from data to support business intelligence and decision support systems.
This course develops your ability to extract meaningful insights from large datasets through the knowledge discovery process. You'll learn to apply data mining algorithms—including classification, clustering, association rules, and predictive analytics—using specialized software tools. Through hands-on projects with real business datasets, you'll develop proficiency in building predictive models and translating technical findings into business recommendations.
Upon completion, students will be able to:
Understand key concepts and trends in data mining
Explore tools and software used for data mining solutions
Apply data mining techniques within decision support systems
Gain practical experience through hands-on exercises
What is business analytics?
Business analytics transforms data into actionable insights through descriptive, predictive, and prescriptive methods. It includes statistical analysis, forecasting models, optimization techniques, and data visualization. This discipline supports data-driven management decisions by identifying patterns, forecasting outcomes, and recommending strategic actions.
This course will develop your quantitative skills for data-driven decision-making in business contexts. Learn to use optimization methods to find the best solutions for resource allocation problems, apply simulation techniques to model complex scenarios under uncertainty, and leverage data mining tools to extract insights from business data.
Upon completion, students will be able to:
Articulate the strategic role of analytics, differentiate between spreadsheets and relational databases and set up a professional analytics environment using Python, R and SQL
Design relational databases, write advanced SQL queries and explain data warehouse architecture
Apply statistical methods and data visualization techniques to summarize business data and communicate insights
Build and evaluate predictive models including regression, forecasting and classification
Formulate business problems using optimization and simulation to recommend strategic actions
What is advanced data mining?
Advanced data mining applies sophisticated techniques including machine learning algorithms, ensemble methods, neural networks, and deep learning. It analyzes unstructured data through text analytics and uses distributed computing for big data. These methods solve complex business problems through advanced pattern recognition.
This course builds on foundational data mining knowledge with advanced techniques for decision support systems and complex analytical challenges. You'll learn ensemble methods like random forests and gradient boosting to improve model accuracy, apply deep learning and neural networks for sophisticated pattern recognition, and use text analytics to mine insights from unstructured data.
Upon completion, students will be able to:
Apply advanced data mining techniques to support decision-making
Build and evaluate predictive models using structured data
Analyze and interpret outcomes from various modeling approaches
Use data-driven insights to inform strategic decisions in uncertain environments
Students must select three courses (nine credit hours) from other tracks within the M.S. in Applied Digital Technology program or advisor-approved courses in business and statistics.