CIP: 110199
Program Description:
The Master of Science in Data Analytics program is designed for those who want to learn how to locate, extract, and transform data into meaningful information by using appropriate analytic tools. Students will learn to apply descriptive and prescriptive analytic techniques in order to inform data-driven business decisions.
Program Outcomes:
Identify and evaluate moral and ethical issues in the analysis of data.
Select the appropriate analytic tools to perform data analytics to help make informed decisions.
Locate, extract, and transform raw data into more useful information.
Apply descriptive and prescriptive analytic techniques to business problems.
Construct and present compelling visuals to communicate a data-driven story.
Plan and execute a real-world project using the steps of the data analytics life cycle.
Program Admissions Criteria:
Bachelor’s degree from an accredited college or university with a 2.75 overall undergraduate GPA and one of the following:
- 3 years of full-time work experience or
- GMAT score of 440 or GRE score of 285
Although students from any undergraduate background are eligible for admission to this program, the M.S. in Data Analytics will require becoming familiar with some technical knowledge or skills including awareness of basic scripting or programming as well as how data are collected, processed, stored, analyzed, and presented. Students are encouraged to visit the web-page for more information on this basic knowledge and skills.
Applicants who do not meet these requirements may be admitted by considering the full academic profile and/or professional experience. The GRE is optional but could be used to improve standing for admission to the program. A Master’s degree from an accredited institution with at least a 3.0 GPA could also be used to meet entrance requirements. The Computer Science and Information Systems unit reserves the right of final decision in accepting students to graduate degree candidacy. Criteria for admittance to the program and acceptance to degree candidacy may include academic qualifications and performance, number of applicants and available resources.
Some three-year undergraduate degrees are accepted as well. In countries that utilize the backlog system in higher education, students with excessive backlogs may be considered with a GRE score to improve standing for admission. Current information on backlog limits can be found on the CSIS web page.
Research/Professional Component:
All graduate students must complete a research or professional development component as part of their requirements for graduation. Students in the M.S. in Data Analytics program will complete a professional development experience in the CSIS 44688 - Data Analytics Capstone Project course.
