Master of Science in Data Analytics
Master of Science in Data Analytics
Be a Data Driven Leader
Accepting Applications Now!
Complete your degree in 12 months!
Are you a data-minded leader who believes that ethical interpretation of data makes a difference in business? We believe this, and that’s why we are committed to supporting you as you seek and live in response to truth. Our Master of Science in Data Analytics prepares graduates for a successful career in the in-demand field of Data Analytics by providing a strong foundation in data analysis, problem solving, and strategic thinking. Based in Catholic social thought, this program provides the knowledge and skills you’ll need to thrive in the business world including decision intelligence, data mining, programming, and more. Together, we’ll explore how decisions are made and how outcomes are evaluated, managed and improved by evidence. The Master of Science in Data Analytics program encourages students to challenge realities often taken for granted, foster intellectual breakthroughs, and cultivate habits of mind that will transform them and communities in which they work and serve.
Possible career paths:
Vice President Level Roles, Strategy Director, Diversity Director, Director of Operational Excellence, Business Intelligence Manager, Strategic Business Intelligence Analyst, Data Scientist, Strategic Advisory Consultant
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$100k
Average Salary for Business Analysts
Program Details
Total Required Credit Hours: 30
- SA 600: Introduction to Strategic Decision Intelligence
- MAL 602: Christian Ethics & Effective Leadership for the Common Good
- SA 610: Introduction to Applied Statistics & Data Analysis
- SA 620: Data Management & Data Mining
- SA 625: Advanced Data Analysis
- SA 630: Data Visualization
- SA 640: Program Evaluation
- SA 650: Grant & Proposal Writing
- SA 660: Leading in a Data-Driven Organization
- SA 665: Analytics Capstone Seminar
It is the student’s responsibility to see that all degree requirements for graduation are fulfilled.
- $695 per credit hour (30 total credit hours)
Admission to the program is determined by evaluating a combination of factors. These factors include:
- Undergraduate GPA; Although there is no minimum undergraduate GPA to apply, GPAs of 3.0 or higher are generally expected.
- Students without prior course work in quantitative methods may need to complete foundational coursework in this area.
- Statement of purpose for pursuing the MS in Data Analytics (optional)
International students whose primary language is not English must demonstrate English Language Proficiency according to College approved methods and thresholds ( For example, minimum TOEFL score—89 IBT)
NOTE: Admission entry point in both fall and spring semesters.
Students may enroll part-time and for a two year completion cycle, but the pathway presented in this document assumes full-time enrollment, including the summer term.
This is a fully online program that can be completed within 12 months or 1 calendar year.
Students may enroll part-time and for a two year completion cycle, but the pathway presented in this document assumes full-time enrollment, including the summer term.
- Completion of MS Capstone Project (3 credit hours) during final semester with approval of written report and successful delivery of oral presentation to combined faculty and workplace audience.
- Total Credits Required for Graduation = 30 credit hours with no more than six credit hours transferred into BAC.
- No more than 2 C course grades in all graduate level coursework with a minimum cumulative GPA of 3.0 combined program course work. Students must achieve a grade of B or higher in the Capstone course.
- Completion of all required coursework within seven years after program admission.
Virtual Office Hours
Tuesdays & Thursdays
12:00 PM – 12:30 PM EST
We’re excited to offer Virtual Open Office Hours with a Graduate Admissions Representative. Whether you have questions about the application process, our programs, or financial aid, we’re happy to assist you in a relaxed and convenient virtual setting.
