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.
Full-time
The W. P. Carey School of Business prepares tomorrow's business leaders to create positive global change through excellence and innovation. Ranked #1 for online undergraduate business programs by U.S. News & World Report (2023) and #10 globally for its Executive MBA by Financial Times (2022), W. P. Carey is a leader in business education.
The school is also highly recognized for its operations, supply chain logistics and project management programs. W. P. Carey sparks positive change by educating students, producing groundbreaking research and engaging with communities to transform the world.
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.
*Transfer eligibility is subject to student performance in courses at home institution 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.
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 |