Program Overview
| Program Coordinator | Aaron Hines, (845) 257-2968, hinesa@newpaltz.edu |
| Program ID | 263 |
| Concentrations | Accounting (263A), Business Intelligence (263B), Healthcare (263H) |
| Credits | 30-36 |
| Program Length | The MS Business Analytics program may be completed full-time in nine months. Students needing foundation courses may complete the program within one-year; however, the degree must be completed within 7 years. |
| Modality | In-person or Online -- all courses are taught in a Hyflex modality where instruction is simultaneously delivered to students in a seated class as well as online. |
| Full-time/Part-time | Full-time (15-credits/term) |
| Transfer Credits | 6 |
Program Description
Business Analytics is the science of turning data into meaningful information that a business could use to its competitive advantage. The proposed M.S. in Business Analytics program will develop business professionals proficient at extracting business value from data. The program focuses on the development of core analytics skills and emphasizes the application of analytics in business areas from accounting to marketing and across industries from healthcare to sports.
Admission Requirements
Applicants to the MS Business Analytics program must submit:
- One official copy of all undergraduate (four-year degree) and graduate coursework, including a baccalaureate degree from an accredited institution.
- An undergraduate cumulative grade point average of 3.0 or higher (4.0 basis). Applicants with a GPA below 3.0 may apply for conditional admission, but should be prepared to provide GMAT or GRE scores if requested. A satisfactory test score of 450 or better on the Graduate Management Admissions Test (GMAT) or 300 or better on the Graduate Record Examination (GRE).
- Three current letters of recommendation
- Statement of objectives
- Prospective international students for whom English is not the native language, and any applicant whose undergraduate degree is from a country where English is not the main language of instruction, are required to demonstrate English language proficiency: minimum TOEFL iBT score of 74, or equivalent (IELTS 6.0). Students may be granted conditional admission without the minimum English proficiency requirement for direct admission if they meet the academic requirements. They can matriculate and begin full-time academic studies once they complete the highest level of the Pathway Program.
- Entering MS students are expected to have competency in basic computer, quantitative, and oral and written communication skills. Students who need to acquire these skills will be advised to take additional credit or non-credit courses to obtain these skills. Any credits taken to obtain basic skills may not, however, be applied toward the MS degree.
- Entering MS students who have earned a "B" or better in statistics and Python or the equivalent to the corresponding courses at New Paltz may have these foundational courses waived. Students without these credits will take foundation courses before starting the program. Students who have no prior credits in statistics will take BUS509, while Python programming can be met by taking BUS601. Both courses are offered during the summer and online.
MS Business Analytics Curriculum
| Code | Title | Credits |
|---|---|---|
| Foundation Courses (0-6 credits) (0 Credits) | 0-6 | |
| 0-6 credits depending upon prior coursework | ||
| Statistics Analysis & Decision Theory | ||
| Python Programming for Analytics | ||
| Core Courses (21 Credits) | ||
| BUS611 | Advanced Statistics for Business Analytics | 3 |
| BUS612 | Data Wrangling and Visualization | 3 |
| BUS615 | Data Warehousing and Big Data | 3 |
| BUS621 | Text Analytics | 3 |
| BUS631 | Machine Learning | 3 |
| BUS632 | Data Mining | 3 |
| BUS638 | Deep Learning | 3 |
| Select a Concentration: (0 Credits) | 9 | |
| Course lists for each concentration area are below. | ||
Accounting | ||
Business Intelligence | ||
Healthcare | ||
| Total Credits | 30-36 | |
Accounting Concentration (263A)
| Code | Title | Credits |
|---|---|---|
| Accounting Concentration (9 Credits) | ||
| BUS581 | Accounting Information Systems | 3 |
| BUS616 | Forensic Accounting | 3 |
| BUS617 | Accounting Data Analytics | 3 |
| Total Credits | 9 | |
Business Intelligence Concentration (263B)
| Code | Title | Credits |
|---|---|---|
| Business Intelligence Concentration (9 Credits) | ||
| Choose three from: | 9 | |
| Spreadsheet for Business Analytics | ||
| Sport Analytics | ||
| Advanced Healthcare Analytics | ||
| Social Network and Web Analytics | ||
| Time Series and Forecasting | ||
| Customer Analytics | ||
| Natural Language Processing | ||
| Total Credits | 9 | |
Healthcare Concentration (263H)
| Code | Title | Credits |
|---|---|---|
| Healthcare Concentration (9 Credits) | ||
| BUS626 | Advanced Healthcare Analytics | 3 |
| Choose two from: | 6 | |
| Health Care Finance | ||
| Healthcare Policy | ||
| Healthcare Management and Leadership | ||
| Total Credits | 9 | |
Graduation Checklist
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Apply for graduation via my.newpaltz.edu under “Graduation” tab according to the schedule in the academic calendar.
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Resolve any pending admission conditions (outlined in your acceptance letter) and/or missing documents if applicable.
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Review your progress report via my.newpaltz.edu to ensure that you have completed all program requirements.
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Remember that only two grades below a B- may be applied to your plan of study
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Contact your advisor if you need to amend your plan or process transfer credit.
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Ensure that you are in good academic standing with a GPA (Grade Point Average) of 3.0 or higher.
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Complete your degree within the specified time limit outlined in the Program Overview.
Program Learning Objectives
Graduates of the MS in Business Analytics will be able to:
- Understand the different forms of analytics and develop a sound understanding of the methods used in each.
- Develop hands‐on experience with analytical tools and software that are widely used in practice including emphasis on Python, SQL, no-SQL, Tableau, and other current and trending technologies.
- Apply analytics in different business domains to enhance decision making.
- Understand the dynamics of leading and participating in successful analytics teams and projects.
