Master of Science in Applied Business Analytics online
Optimize your career by helping organizations extract maximum benefit from big data. Gain the cutting-edge skills to drive business growth by transforming raw data into effective, actionable insights.
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Program Overview
Discover the benefits of our master’s in applied business analytics online program.
$17,872.50
Total Tuition
As few as 12 months
Duration
30*
Credit Hours
As data accelerates in both volume and complexity and commerce has become increasingly globalized, the need is greater than ever for those who can effectively use big data to solve business issues. The online Master of Science in Applied Business Analytics program will empower you with next-generation quantitative skills and strategies, preparing you for advanced roles in a wide range of organizations.
This rigorous, skills-focused program spans the full scope of business analytics, from data mining and visualization to machine learning and multivariate statistics. Learn from top-tier industry experts as you master the use of descriptive, predictive, and prescriptive analytics to identify trends and steer business growth toward desired outcomes.
As a graduate of this program, you will be able to:
- Understand and manage big data to identify insights and drive solutions
- Use the appropriate tools, techniques, and strategies for successful analytics solutions
- Analyze situations and perform real-world data simulations using industry-trending technologies such as R, Tableau®, Python™, and more
- Utilize data visualization to communicate findings effectively to diverse target audiences
- Understand and manage big data to identify insights and drive solutions
- Use the appropriate tools, techniques, and strategies for successful analytics solutions
- Analyze situations and perform real-world data simulations using industry-trending technologies such as R, Tableau®, Python™, and more
- Utilize data visualization to communicate findings effectively to diverse target audiences
Strengthen your mastery of in-demand skills, technologies, methodologies, and platforms, including:
- Big data
- Python
- Tableau
- Business intelligence
- Data visualization
- Predictive analytics
- Data mining and warehousing
- Multivariate analytics
- Machine learning
- Cybersecurity
- Marketing analytics
- Artificial Intelligence
- Big data
- Python
- Tableau
- Business intelligence
- Data visualization
- Predictive analytics
- Data mining and warehousing
- Multivariate analytics
- Machine learning
- Cybersecurity
- Marketing analytics
- Artificial Intelligence
Career opportunities:
- Controller
- Data Engineer
- Data Scientist
- Senior Financial Analyst
- Business Intelligence Analyst
- Senior Data Analyst
- Controller
- Data Engineer
- Data Scientist
- Senior Financial Analyst
- Business Intelligence Analyst
- Senior Data Analyst
Graduate programs also available:
William Paterson University offers a variety of master’s-level programs. Check out all of our online graduate programs.
$17,872.50
Total Tuition
As few as 12 months
Duration
30*
Credit Hours
William Paterson University’s Cotsakos College of Business is accredited by The Association to Advance Collegiate Schools of Business (AACSB International).
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Tuition
Explore the value of our budget-friendly tuition.
The business analytics online program from William Paterson University offers affordable, pay-by-the-course tuition. All fees are included in the total tuition.
Tuition breakdown:
$17,872.50
Total Tuition
$595.75
Per Credit Hour
| Program | Per Credit Hour | Per Course | Per Program |
|---|---|---|---|
| MS in Applied Business Analytics | $595.75 | $1,787.25 | $17,872.50 |
Tuition breakdown:
$17,872.50
Total Tuition
$595.75
Per Credit Hour
Calendar
Set a calendar reminder for these key deadlines.
William Paterson University online programs are delivered in an accelerated format ideal for working professionals, conveniently featuring multiple start dates each year.
Now enrolling:
1/5/25
Apply Date
1/27/25
Class Starts
| Term | Start Date | App Deadline | Document Deadline | Registration Deadline | Tuition Deadline | Class End Date | Term Length |
|---|---|---|---|---|---|---|---|
| Fall II | 11/4/24 | 10/14/24 | 10/16/24 | 10/25/24 | 10/30/24 | 12/22/24 | 7 weeks |
| Spring I | 1/27/25 | 1/5/25 | 1/8/25 | 1/17/25 | 1/22/25 | 3/16/25 | 7 weeks |
| Spring II | 3/24/25 | 3/2/25 | 3/5/25 | 3/14/25 | 3/19/25 | 5/11/25 | 7 weeks |
| Summer I | 5/19/25 | 4/27/25 | 4/30/25 | 5/9/25 | 5/14/25 | 7/6/25 | 7 weeks |
| Summer II | 7/14/25 | 6/22/25 | 6/24/25 | 7/3/25 | 7/9/25 | 8/31/25 | 7 weeks |
| Fall I | 9/8/25 | 8/17/25 | 8/20/25 | 8/29/25 | 9/3/25 | 10/26/25 | 7 weeks |
| Fall II | 11/3/25 | 10/12/25 | 10/15/25 | 10/24/25 | 10/29/25 | 12/21/25 | 7 weeks |
Now enrolling:
1/5/25
Apply Date
1/27/25
Class Starts
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Admissions
Follow these steps to apply to the MS in Applied Business Analytics online.
At William Paterson University, we’ve streamlined the admission process to help you get started quickly and easily. Please read the requirements for the MS in Applied Business Analytics online, including what additional materials you need and where you should send them.
The requirements include:
- Undergraduate degree from an accredited institution
- GPA of 2.75 or higher
- Transcripts from all colleges and universities previously attended
- Professional resume detailing educational and work experience
You must meet the following requirements for admission to the MS in Applied Business Analytics online program:
- Submit online application and $50 application fee
- Successful completion of a graduate or undergraduate degree from an accredited program in any of the following: Business, Math, Computer Science, Statistics, Healthcare, Psychology, Sociology, Biosciences, Engineering, or similar quantitative, scientific and technology programs
- Mathematical proficiency is required: Academically or professionally demonstrated quantitative skills and aptitude are necessary as evidenced by an appropriate academic degree or relevant work experience and accomplishments, or qualifications (such as a list of quantitative/technology courses taken)
- Cumulative undergraduate GPA of 3.0 or higher OR ability to provide evidence of potential success by providing:
- Cumulative undergraduate GPA of 2.75-2.99 with:
- Two years of relevant work experience and demonstrated mathematical proficiency OR
- 90th percentile scores in GMAT or GRE
- Professional resume detailing educational and work experience
- International students and U.S. students who have non-U.S. academic credentials should follow WP’s graduate admission requirements
- Official transcripts from all colleges and universities attended
Official transcripts, test scores, and other documents should be sent from the granting institutions to:
Email address: [email protected]
Mail address:
Office of Graduate Admissions and Enrollment Services
William Paterson University
Morrison Hall 102
300 Pompton Road
Wayne, NJ 07470
Courses
Preview the study topics of the MS in Applied Business Analytics courses.
For the MS in Applied Business Analytics online, you must complete 18 credit hours of core courses (including a capstone course), 6 credit hours of foundation courses, and 6 credit hours of electives.
BAN 5100: Data Visualization and Inferential Business Statistics
Duration: 7 Weeks weeks
Credit Hours: 3
This course serves as a hands-on introduction to basic statistical concepts and the ways to communicate them to the target audience. Currently, businesses encounter tremendous challenges to process and utilize the vast amounts of different types of data generated as a result of customer and business activities. This class introduces the fundamental elements of inferential statistics and supplements it with visualization techniques to show students how to learn, analyze, and present data. The focus on inferential statistics will enable students to describe data, evaluate samples, and perform hypotheses testing. Visualization techniques will help students communicate their findings in the form of reports and presentations.
BAN 5600: Business Applications Using Python
Duration: 7 Weeks weeks
Credit Hours: 3
This course includes the principles of programming and software development using Python programming language. This class emphasizes the applications of computer programming based on real-life examples in various fields of business including Business Analytics, Management, Marketing, Finance, among others. Upon completion of the course, students will be able to understand computational concepts in addition to the fundamentals of the Python programming language. In addition, this course will cover the manipulation and use of data to solve businesses problems. In this course, students will be introduced to software packages for data manipulation and development of solutions to statistical and mathematical problems. In addition, we will apply machine learning and statistical methods to data obtained from online sources.
BAN 7010: Business Analytics for Decisions
Duration: 7 Weeks weeks
Credit Hours: 3
This course explores business analytics concepts and applications aimed at improving business performance. The course focuses on the three facets of analytics: Descriptive Analytics, Predictive Analytics, and Prescriptive Analytics. An integral part of business analytics is the use of IT tools to support the collection and analysis of data, and converting it into actionable knowledge in the context of organization decision-making and problem solving. As such, the students will learn problem analysis and formulation, data modeling, data mining, and the application of various business analytics and spreadsheet tools.
BAN 7100: Data Warehousing and Data Mining
Duration: 7 Weeks weeks
Credit Hours: 3
This course covers two related topics in the age of big data and knowledge discovery: data warehousing and data mining — their concepts, principles, and techniques. Topics in data warehousing include data warehouse/data mart architecture; multi-dimensional model design; extracting, transforming, and loading strategies. Topics in data mining range from statistics to machine learning; including techniques of clustering, association rules, and classification. OLAP (On-Line Analytical Processing) applications and business intelligence are also introduced.
BAN 7300: Multivariate Statistics
Duration: 7 Weeks weeks
Credit Hours: 3
A comprehensive analysis of single and multivariable functions. Topics include limits, derivatives and partial derivatives, extreme values, integrals, and differential equations. Possible applications of mathematical techniques will be emphasized.
BAN 7700: Machine Learning
Duration: 7 Weeks weeks
Credit Hours: 3
This course is designed to provide a broad overview of machine learning concepts and applications aimed at automating and advancing analytics performance. The course distinguishes itself by anchoring its content on big data phenomena and thus domain knowledge, technology, and math are integrated throughout the course. The course covers five broad segments of topics in machine learning driven analytics: Fundamentals (Algebra, Matrices, and Probability for ML), algorithms (Optimization Techniques), supervised learning, unsupervised learning, and managerial application (Thought Leadership and usage of ML in big-data analytics). This course provides a unique balance between theory and application along with data driven cases — thus it aims to impart expert skills along with encouraging thought leadership. An integral part of machine learning analytics is the use of IT tools to support the organization and analysis of data — hence the students will learn to apply various machine learning analytics tools including R.
BAN 7800: Artificial Intelligence
Duration: 7 Weeks weeks
Credit Hours: 3
This course provides a practical introduction to concepts, processes, and methods deployed in the field of artificial intelligence (AI). AI applications are currently deployed in a vast range of business activities for the purpose of employee vetting, answering customer queries, target marketing, predicting and assessing loan risks, warehouse management, and customer delivery management. Upon completion of this course, students will be able to understand AI processes and apply analytics tools such as Python and R to solve business problems and develop applications.
BAN 8000: Capstone - Integrated Experiential Practicum
Duration: 7 Weeks weeks
Credit Hours: 3
This course is designed to prepare all MS in Business Analytics candidates for their professional careers through the integration and application of their course learnings in the development of a solution to a selected real world business problem. Specifically, students will develop an experiential learning project where they apply business analytics skills in their area of professional interest. Students may choose to investigate an issue at their place of work or undertake research that will lead them to new fields. The capstone experience will provide students with direct experience in business analytics by solving a real problem.
BAN 7150: Cybersecurity and Information Assurance
Duration: 7 Weeks weeks
Credit Hours: 3
This course will educate existing and future business managers and IT Professionals on best practices and processes in the information security management. The course explores this subject starting with a review of the fundamentals of Cybersecurity and Cybercrime then progressing through laws and ethics of information compliance, information security governance & policies, planning & management, assessing & controlling risk and long term planning and management of mechanisms of privacy and security.
BAN 7450: Marketing Analytics
Duration: 7 Weeks weeks
Credit Hours: 3
This course is designed to provide a useful conceptual framework as well as analytical techniques that can be applied in developing effective marketing strategies in the era of Big Data. The key areas of marketing analytics focus on product analytics, pricing management, customer analytics, and web analytics. Specific topics to be covered include market segmentation, assessing value to the customer, customer lifetime value, social media analytics, and related topics.
*Students without pre-requisite foundation courses may require additional credits.
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