Best Graduate Schools for Data Science & Business Analytics
The Data Science & Business Analytics ranking compares universities for graduate study using subject strength and applicant demand. This page shows positions 1–30 from the full ranking. Each position belongs to a university, not an individual degree program. Open a university's program count to see and compare its matching graduate programs. It covers professional master's programs in data science and business analytics, with emphasis on technical training and employment outcomes.
How this ranking is built
Graduate study is a career decision. These subject rankings help applicants compare where a degree may create the strongest long-term value, using evidence that reflects how graduate students actually choose and what they gain from their degrees.
We build subject rankings across 37 disciplines and publish the top 30 universities in each. Each university receives one position in the published table for that subject. That position reflects how the university performs across key ranking components, combined consistently for every institution in scope.
Key ranking components
- Research strengthDepth, quality, and influence of scholarship and faculty in the university or field.
- Employability and career outcomesGraduate placement, employer access, professional standing, alumni networks, and long-term options created by the degree.
- Global engagementInternational reach, cross-border relevance, and breadth of academic and professional networks.
- Learning experienceQuality and breadth of graduate study and the environment in which students learn, collaborate, and develop.
- Applicant demand and revealed preferenceApplication demand and choices admitted applicants make when they hold more than one offer.
Independent expert judgment calibrates the weight given to each component and checks that the resulting order makes sense. There is no one-size-fits-all balance across subjects: research-led fields place more emphasis on academic depth, while professional fields place more emphasis on career outcomes and professional training.
Questions About the Data Science & Business Analytics Ranking
- What does the Data Science & Business Analytics ranking measure?
- It compares the strength of graduate study in Data Science & Business Analytics across universities using key ranking components: research strength; employability and career outcomes; global engagement; learning experience; and applicant demand and revealed preference. Independent expert judgment calibrates the weight given to each component for the field and checks that the resulting order makes sense.
- Does the Data Science & Business Analytics ranking compare universities or individual programs?
- The ranking compares universities, not individual programs. Each university receives one position based on how its graduate offering in Data Science & Business Analytics performs across the key ranking components. Individual programs do not receive separate ranks.
- How should I use the Data Science & Business Analytics ranking to build my shortlist?
- Use it to identify universities worth investigating, then compare their programs for academic fit, admissions requirements, deadlines and costs. A higher position should inform your shortlist, not decide it for you.
- Which countries are represented in the Data Science & Business Analytics ranking?
- United States (20), United Kingdom (6), Canada (1), China (1), Singapore (1), and Switzerland (1). The ranking is global and does not use a country quota.
- Are higher-ranked universities usually harder to get into?
- Often, but not always. Applicant demand and revealed preference are only part of the ranking. Research strength, career outcomes, global engagement, learning experience and field-specific calibration also shape the order. Admission standards still vary by degree level, specialization and individual program, even within the same university.
Explore Rankings and Programs
Browse Subject Rankings
The complete Grad School Navigator subject ranking directory, grouped by field.
Engineering
Business and Management
Computing and Data
- Artificial Intelligence
- Computer Science
- Data Science & Business Analytics