The W. P. Carey MS in Business Analytics is a STEM-designated program emphasizing the importance of data in today’s world. It prepares students for careers in business analytics by teaching them to extract value from data, manage data-driven projects, and impact businesses.
The program offers five specializations: Big data, cloud computing and tech consulting, fintech, marketing analytics, and supply chain analytics. Available in two formats, the full-time program lasts 9 or 16 months based on the chosen track, and the online option caters to working professionals seeking to advance their skills without pausing their careers.
Quick Facts
Full-time
30 credit hours
Campus or Online Immersion
Tempe campus
STEM-OPT Option Available
Students enrolled at an ASU Cintana Alliance Network institution have the chance to start their courses at their home institution and transfer those credits* to finish their remaining years at ASU.
Models available: Graduate dual degree and accelerated masters.
CIS 505: Enterprise Data Analytics (3)
CIS 591: Python for Data Analysis (3)
SCM 516: Descriptive and Predictive Analytics (3)
SCM 517: Business Process Analytics (3)
Required Core (3)
CIS 509: Analytics for Unstructured Data
Electives (12)
Culminating Experience (3)
CIS 593: Applied Project (1.5)
SCM 593: Applied Project (1.5)
Additional Curricular Information – For electives, students should consult the academic unit for a list of approved courses.
*Transfer eligibility is subject to student performance in bridge courses and Arizona State University transfer requirements.
Ensuring the foundational understanding of contextualized analytics within the business enterprise continuum by covering how data flows and is managed across the landscape of enterprise business processes.
Deep learning applications have become an integral part of our lives over the last decade. Alexa, Amazon Go, Waymo, Apple Face ID, and Facebook's face recognition applications are all powered by deep learning networks. Applications based on deep learning models cover a wide spectrum of industries including retail, automotive, manufacturing, health care, banking, insurance, agriculture, security and surveillance. Hands-on look at the latest models, trends and challenges of deep learning applications in business.
Provides a solid foundation and deeper understanding of the use of quantitative modeling tools and techniques to solve problems faced in modern supply chains. Uses Excel workbooks to implement the appropriate quantitative methods, including forecasting demand, capacity planning of a manufacturing line and the line cycle time as it pertains to parts inventory management.
Graduates have the essential academic preparation required for roles that derive value from data and modeling, lead data-driven analyses and that create critical business advantages.
The U.S. Bureau of Labor Statistics’ Occupational Outlook Handbook (2019) states, employment for business intelligence analysts is projected to grow between 7% and 10% between 2018 and 2028, faster than average.
Applicants are eligible to apply to the program if they have earned a bachelor’s or master’s degree from a regionally accredited institution.
Official transcripts from every college or institution attended, including your current institution. Must submit original transcripts and English translated transcripts.
Minimum GPA of 3.00 (scale is 4.00 = “A”) in the last 60 credit hours of their first bachelor’s degree program, or applicants must have a minimum cumulative GPA of 3.00 (scale is 4.00 = “A”) in the last 12 units of the postbaccalaureate transcript.
Applicants are required to submit:
A letter of recommendation. The letter of recommendation should comment on the student’s motivation, commitment, achievements, work experience and opportunity for success in the program.
Short answer question responses.
A professional resume or curriculum vitae.
Proof of English proficiency: (TOEFL>80 iBT or >500? (paper-based), IELTS>6.5, Pearson Test of English>60, Duolingo>105), or a passing score in the English for Graduate Admission online course through ASU Global Launch. All taken within the last two years from start date.
| Enrollment Path MS Business Analytics | Credit Hours Completed at Institution | Credit Hours Completed at ASU | Estimated Duration | Total Program Cost |
|---|---|---|---|---|
| Articulated Pathway (ASU Cintana Alliance) | 12 | 18 | 1 year (2 semesters) | Campus Immersion: ~$47,650, Online: ~ $25,243 |
| Direct ASU Enrollment (International student) | 30 | 1.5 - 2 years (3-4 semesters) | Campus Immersion: ~$78,151, Online: ~$42,038 |
Note 1: This is an estimate only. Based on ASU 2024-25 published tuition and fee rates. Subject to change for future years.
Note 2: Tuition calculation for Articulated Pathway based on 9 credits (Fall), 9 credits (Spring). For all other tracks is based on 12 credits (Fall), 12 credits (Spring) and 7 credits (Summer or Fall).
| Program Start | Application Deadline | Classes Begin | Tuition Payment Deadline |
|---|---|---|---|
| Spring start (January) | November 28, 2024 | January 13, 2025 | January 20, 2025 |
| Fall start (August) | July 1, 2025 | August 21, 2025 | August 25, 2025 |
| Spring start (January) | November 28, 2024 | January 12, 2026 | January 19, 2026 |