Business Analytics MS

Contact

Don Harter, Associate Professor of Management Information Systems; 517 Whitman School of Management, 315-443-3502, dharter@syr.edu

Program Description

The MS in Business Analytics challenges students to develop an interdisciplinary understanding of the applications of analytics to the fields of accounting, finance, marketing, and supply chain management through techniques in data collection, data visualization, statistical and pattern analysis, and data mining. The curriculum leverages an understanding of business applications from the Whitman School of Management combined with in depth technical offerings of the School of Engineering and Computer Science and the School of Information Studies.

Accreditation

The Whitman School has been accredited by the Association to Advance Collegiate Schools of Business (AACSB International) since 1920.

Admission

Students are required to take the GMAT as part of the application process. Applicants will be considered for the program based on their GMAT score, previous academic experience, work experience, professional references, and personal statements.

Financial Support

Merit-based financial support is awarded based on a student’s admission application. These awards are highly competitive and are available to both U.S. and international full-time students. Students may apply for several loan programs to cover the cost of attendance. (Federal Direct Loan, ProgramFederal PLUS Loans, Alternative Loan Programs) Part-time students must be enrolled for at least six credits (half-time status) to be considered for loan programs.

Student Learning Outcomes

1. Students will be able to collect and organize data.

2. Students will identify patterns in data via visualization, statistical analysis, and data mining.

3. Students will develop alternative strategies based on the data.

4. Students will develop a plan of action to implement the business decisions derived from the analyses.

Degree Requirements & Learning Objectives

This is a 36 credit program that leads to a Master of Science in Business Analytics degree.

The MS Business Analytics curriculum is designed as a 36-credit program and normally requires two years or four academic semesters to complete on a full-time basis. It consists of four elements: 6 credits of required core courses; 6 credits of Analytics Applications courses; 6 credits of Analytics Depth or additional Analytics Applications courses; and 18 credits of Analytics electives. Students may select electives from other graduate programs in the University.

Required Core Courses and Credits

(both courses required)

MBC 638 - Data Analysis and Decision Making 3 credit(s)
SCM 651 - Business Analytics 3 credit(s)

Analytics Applications Core (select 2)

ACC 652 - Accounting Analytics 3 credit(s)
MAR 653 - Marketing Analytics 3 credit(s)
FIN 654 - Financial Analytics 3 credit(s)
SCM 702 - Principles of Management Science 3 credit(s)

Analytics Depth Core

(Select 2 - can include any not already selected from Analytics Applications)

MAS 766 - Linear Statistical Models I: Regression Models 3 credit(s)
MAS 777 - Time Series Modeling and Analysis 3 credit(s)
MAR 655 - Customer Relationship Management with Systems Applications and Products 3 credit(s)
IST 687 - Introduction to Data Science 3 credit(s)
IST 718 - Big Data Analytics 3 credit(s)
IST 777 - Statistical Methods in Information Science and Technology 3 credit(s)
IST 707 - Data Analytics 3 credit(s)
IST 657 - Basics of Information Retrieval Systems 3 credit(s)
IST 719 - Information Visualization 3 credit(s)
IST 722 - Data Warehouse 3 credit(s)
IST 776 - Research Methods in Information Science and Technology 3 credit(s)
CSE 581 - Introduction to Database Management Systems 3 credit(s)
CSE 787 - Analytical Data Mining 3 credit(s)

Analytics Electives

(Select 6 courses - can include any not selected from above)

IST 659 - Data Administration Concepts and Database Management 3 credit(s)
IST 664 - Natural Language Processing 3 credit(s)
CIS 554 - Object Oriented Programming in C++ 3 credit(s)
CIS 667 - Introduction to Artificial Intelligence 3 credit(s)
CPS 681 - Explorations in Computing and Programming 3 credit(s)
CIS 731 - Artificial Neural Netwks 3 credit(s)
CSE 682 - Software Engineering 3 credit(s)
CIS 685 - Simulation & Modelling 3 credit(s)
Other approved graduate business or analytics courses from Syracuse University

Transfer Credit

Students can transfer a maximum of 6 credits of elective coursework. The credits must be graduate level taken from an AACSB accredited business school. A grade of “B” or higher is needed to transfer in the credits. The grade itself does not transfer.

Satisfactory Progress

Students are required to maintain a GPA of 3.0 or higher to meet degree requirements.

Students must pass a comprehensive exam at the end of the last semester of the program.