State University of New York

What you'll study

This Bachelor in Data Analytics is typically delivered over four years and blends foundational coursework with hands-on labs, projects and an optional capstone or internship. The curriculum emphasises statistical reasoning, computational methods and communication of results for real-world decision making.

• Core quantitative foundations — calculus, linear algebra, probability and mathematical statistics to give the theoretical basis for modelling and inference.
• Programming and software — instruction in languages and environments commonly used in analytics such as Python, R and SQL, plus training in version control and reproducible research tools.
• Statistical modelling and machine learning — regression, classification, clustering, time-series analysis and introductory supervised and unsupervised learning techniques.
• Data engineering and databases — data modelling, relational databases, ETL concepts and an introduction to big-data platforms and cloud-hosted services.
• Data visualisation and communication — principles of visual design, dashboarding tools, storytelling with data and presentation skills for technical and non‑technical audiences.
• Applied analytics electives — domain-specific courses that apply analytics to areas such as finance, healthcare, marketing, urban planning or public policy.
• Capstone/experiential learning — a supervised project or industry internship where students work on an applied analytics problem, often in collaboration with external partners.
• Ethics and professional practice — data privacy, fairness, legal and ethical considerations in collecting and using data.

Entry requirements

Applicants should hold a recognised secondary school diploma or equivalent. Typical preparation includes strong performance in mathematics, such as algebra and precalculus, and coursework in science or computing where available. Admissions commonly consider overall academic record, personal statement and, where submitted, standardised test scores; some SUNY campuses may also request specific prerequisites or placement testing in mathematics.

For applicants whose first language is not English, proof of English proficiency may be required according to the policies of the individual SUNY campus. Mature or transfer students with college-level credits in relevant subjects are usually considered; transfer admissions will assess prior coursework and credits for degree applicability.

Career prospects

Graduates with a Bachelor in Data Analytics are equipped to enter a wide range of roles in the private and public sectors. Common entry-level positions include:

• Data Analyst — analysing datasets, producing reports and dashboards to support business decisions.
• Business Intelligence (BI) Developer — designing and maintaining analytics systems and data visualisations for organisational insight.
• Junior Data Scientist / Machine Learning Assistant — implementing models and contributing to predictive analytics projects.
• Data Engineer (entry-level) — building data pipelines and preparing data for analysis in collaboration with senior engineers.
• Analytic Consultant or Policy Analyst — applying quantitative skills to solve sector-specific problems in finance, healthcare, government and non-profits.

Many graduates also continue to postgraduate study in data science, statistics, computer science or specialised professional fields. The combination of technical skills and applied experience positions students for roles that rapidly increase in responsibility and salary as they gain experience.

Why study at State University of New York

The SUNY system offers a broad network of campuses with access to diverse faculty expertise, research centres and industry connections across New York State. Students benefit from applied learning opportunities such as internships with public agencies and private companies, cross-disciplinary collaborations and access to campus computing resources and labs.

SUNY campuses emphasise affordability and transfer pathways, which can be advantageous for students seeking flexible routes into a data analytics degree. Many campuses maintain career services and employer relationships that support job placement, co‑op programmes and networking events tailored to analytics and technology employers.

Finally, studying within the SUNY system provides exposure to real-world data challenges across urban and regional contexts, enabling students to apply analytics skills to a wide variety of industries and public-interest problems.