Big Data Analytics

Graduate Information

OFFICE: Storm Hall 329
TELEPHONE: 619-594-8555
EMAIL: info.bigdata@sdsu.edu
WEBSITE: https://big.sdsu.edu

Faculty

Committee for Big Data Analytics
Ming-Hsiang Tsou, Ph.D., Professor of Geography, Chair of Committee and Director of Program (Graduate Adviser)
Li An, Ph.D., Professor of Geography
C. Janie Chang, Ph.D., Professor of Accountancy, The Vern E. Odmark Chair in Accountancy
Robert A. Edwards, Ph.D., Professor of Biology
Jean Mark Gawron, Ph.D., Professor of Linguistics
Piotr L. Jankowski, Ph.D., Professor of Geography
Samuel S.P. Shen, Ph.D., Albert W. Johnson Distinguished Professor of Mathematics
Bongsik Shin, Ph.D., Professor of Management Information Systems
Brian H. Spitzberg, Ph.D., Professor of Communication, Emeritus [Senate Distinguished Professor]
Faramarz Valafar, Ph.D., Professor of Public Health
Jianwei Chen, Ph.D., Associate Professor of Statistics
Xiaobai Liu, Ph.D., Associate Professor of Computer Science
Atsushi Nara, Ph.D., Associate Professor of Geography
Bo-Wen Shen, Ph.D., Associate Professor of Mathematics
Jessica Pressman-Lupien, Ph.D., Associate Professor of English and Comparative Literature
Wei Wang, Ph.D., Associate Professor of Computer Science
Ke Huang, Ph.D., Assistant Professor of Electrical and Computer Engineering
Xialu Liu, Ph.D., Assistant Professor of Management Information Systems
Yang Xu, M.S., Assistant Professor of Computer Science
Nancy J. Jones, M.B.A., Lecturer in Accountancy

General Information

The Master of Science degree in big data analytics prepares students with skills to explore and identify research and business opportunities provided by big data across various application domains, such as information technology, geographic information systems (GIS), social and behavioral science, digital humanities, public health, business analytics, and biotechnology.

Students develop competencies in management and analysis of big data applications with appropriate programming tools, statistical models, social theories, business concepts, and analytic software. The program has a dual-core design for students to learn computational skills (programming languages and software) and analytical methods (data mining, machine learning, spatiotemporal analysis, statistics, visualization) for data models and business applications.

Big data analytics is transdisciplinary across business, engineering, science, social science, and technology domains and involves collecting, cleaning, organizing, analyzing, and modeling data for various applications. Students use the outcomes of big data analytics to formulate research hypotheses and guide decision-making in academic or business settings.

The Master of Science degree in big data analytics provides a flexible curriculum framework for students from various backgrounds by customizing individual study plans in different fields to include business analytics, digital humanities, geospatial technology, management information systems, social science, and text analytics. The degree builds a collaborative and active transdisciplinary educational environment for students and professionals who wish to advance their knowledge and skills in the fast growing fields of data science and data analytics.

Admission to Graduate Study

In addition to the general requirements for admission to the university with classified graduate standing, as described in Admission and Registration , applicants must satisfy the following requirements.

Relevant background (including previous coursework) in business, mathematics, computer science, geographic information systems, digital humanities or related fields.
Basic knowledge in computer science and programming, as demonstrated by a grade of C (2.0) or better in CS 107 or equivalent course, or work experience.
Basic knowledge in statistical data analysis, as demonstrated by a grade of C (2.0) or better in STAT 119 or equivalent course, or work experience.

Students applying for admission should electronically submit the university application available at https://www2.calstate.edu/apply along with the application fee.

Graduate Admissions

The following materials should be submitted as a complete package directly to:

Graduate Admissions
San Diego State University
5500 Campanile Drive
San Diego, CA 92182-7416

Official transcripts (in sealed envelopes) from all postsecondary institutions attended;

NOTE:
- Students who attended SDSU need only submit transcripts for work completed since last attendance.
- Students with international coursework must submit both the official transcript and proof of degree. If documents are in a language other than English, they must be accompanied by a certified English translation.
GMAT scores (SDSU institution code 9LT-2P-73) or GRE scores (http://www.ets.org, SDSU institution score 4682);
English language score, if medium of instruction was in a language other than English (http://www.ets.org, SDSU institution code 4682);
One page statement of research interests and professional goals (maximum 500 words).

The following supplemental materials should be submitted to the program via Interfolio.

A current curriculum vitae or resume. Include undergraduate GPA and GRE or GMAT score (IELTS, PTE Academic, or TOEFL, if applicable) with curriculum vitae or resume;
One-page statement of research interests and professional goals (maximum 500 words);
Copies of transcripts from all colleges and universities attended (electronic, photocopies, and unofficial copies are acceptable). Note: This is in addition to transcripts submitted to Graduate Admissions;
Copies of GRE or GMAT score (IELTS, PTE Academic, or TOEFL, if applicable). Electronic, photocopies, and unofficial copies are acceptable. NOTE: This is in addition to transcripts submitted to Graduate Admissions;
One or two letters of recommendation (optional).

Advancement to Candidacy

All students must satisfy the general requirements for advancement to candidacy, as described in Requirements for Master’s Degrees .