Big Data Analytics

Graduate Information

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

Faculty:

Program Director: Tsou, Ming-Hsiang, Professor of Geography, Chair of Committee and Director of Big Data Analytics Program (B.S., National Taiwan University, Taiwan; M.A., State University of New York at Buffalo; Ph.D., University of Colorado at Boulder)

Graduate Advisor: Fernandez, Gabriela, Adjunct Professor of Geography, (B.S. and MCP, San Diego State University; Ph.D., the Politecnico di Milano (POLIMI) in Milan, Italy)

Faculty:

An, Li, Professor of Geography (B.S., Beijing University, China; M.S., Chinese Academy of Sciences, China; Ph.D., Michigan State University)

Gawron, Jean Mark, Professor of Linguistics (B.A., New York University; M.A., Ph.D., University of California, Berkeley)

Jankowski, Piotr L., Professor of Geography (M.S., Poznan University of Economics, Poland; Ph.D., University of Washington)

Lin, Chii-Dean, Professor of Mathematics and Statistics (B.S., National Chiao-Tung University, M.S., New Jersey Institute of Technology, Ph.D., Texas A&M University)

Malouf, Robert, Professor of Linguistics (B.A., State University of New York at Buffalo; Ph.D., Stanford University)

Martinez, Lourdes S., Professor of Communication, Associate Director, Undergraduate Studies (B.A., Johns Hopkins University; M.A., Ph.D., University of Pennsylvania)

Shen, Samuel S.P., Albert W. Johnson Distinguished Professor of Mathematics (B.Sc., Nanjing University of Science and Technology, China; M.A., Ph.D., University of Wisconsin, Madison)

Shin, Bongsik, Professor of Management Information Systems (B.A., Sogang University, South Korea; M.S., Bernard M. Baruch College, The City University of New York; Ph.D., University of Arizona)

Valafar, Faramarz, Professor of Public Health (Vordiplom, Kaiserslautern University, Germany; M.S., Michigan Technological University; Ph.D., Purdue University)

Wang, Wei, Professor of Computer Science (B.S., M.A., Xian Jiaotong University, China; Ph.D., University of Nebraska)

Bani Younes, Ahmad, Associate Professor of Aerospace Engineering (B.S., Jordan University of Science and Technology, Jordan; M.S., University of Dayton; Ph.D., Texas A&M University)

Beck, Audrey N., Associate Professor of Sociology (B.A., University of California, Los Angeles; M.A., Ph.D., Duke University)

Chen, Jianwei, Associate Professor of Statistics (B.S., National Huaqiao University, China; M.S., Ph.D., Chinese University of Hong Kong, Hong Kong)

Elkins, Aaron C., Associate Professor of Management Information System (B.S., San Diego State University; Ph.D., University of Arizona)

Goldberg, David M., Associate Professor of Management Information Systems (B.S., Ph.D., Virginia Polytechnic Institute and State University)

Huang, Ke, Associate Professor of Electrical and Computer Engineering (B.S., M.A., Joseph Fourier University, France; Ph.D., University of Grenoble, France)

Liu, Xialu, Associate Professor of Management Information Systems (B.S., Zhejiang University, China; M.A., Peking University, China; Ph.D., Rutgers University)

Liu, Xiaobai, Associate Professor of Computer Science (B.S., Fudan University, China; Ph.D., Huazhong University of Science and Technology, China)

Nara, Atsushi, Associate Professor of Geography (B.S., Shimane University, Japan; M.S., University of Utah; Ph.D., Arizona State University)

Shen, Bo-Wen, Associate Professor of Mathematics (B.S., M.S., National Central University, Taiwan; Ph.D., North Carolina State University)

Xu, Yang, Associate Professor of Computer Science (B.S., M.S., Tsinghua University, China)

Huangfu, Luwen, Assistant Professor of Management Information System (B.S., Chongqing University; M.S., Chinese Academy of Sciences; Ph.D., University of Arizona)

Jahangiri, Arash, Assistant Professor of Department of Civil, Construction, and Environmental Engineering, (Ph.D., Virginia Tech)

Paternina-Arboleda, Carlos D., Assistant Professor of Management Information System (Ph.D., University of South Florida)

Xu, Shengjie, Assistant Professor of Management Information System (M.S., University of Pittsburgh, Ph.D. University of Nebraska-Lincoln).

Emeritus Faculty:

Chang, C. Janie, Professor of Accountancy, The Vern E. Odmark Chair in Accountancy and William E. Cole Director (B.B.A., Tamkang University, Taiwan; M.S., University of Illinois at Chicago; Ph.D., University of California, Irvine)

Spitzberg, Brian H., Ph.D., 1989-2018, Professor of Communication [Senate Distinguished Professor]

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 150 and CS 150L 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

After you have submitted the Cal State Apply application, the following materials should be submitted as a complete package directly to:

Graduate Admissions Office
San Diego State University
5500 Campanile Drive
San Diego, CA 92182-8225

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.
A GRE or GMAT score is required only for applicants with an undergraduate GPA of below 3.2 or with a degree in a non-quantitative field, so that the applicants can demonstrate the requisite quantitative knowledge. GRE scores (http://www.ets.org, SDSU institution score 4682), GMAT scores (SDSU institution code 9LT-2P-73);
English language score (TOEFL, IELTS, Duolingo English Test, or PTE), are required of applicants, regardless of citizenship, whose native language is not English and whose preparatory education was principally in a language other than English. A minimum TOEFL (SDSU institution code 4682) score of 80 is required. Scores should be sent directly from ETS using SDSU’s Institution Code 4682. Applicants may also take the IELTS in lieu of the TOEFL and must present a minimum score of 6.5. Applicants may also take the PTE in lieu of the TOEFL and must present a minimum score of 58.

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

One page statement of research interests and professional goals (maximum 500 words);
A current resume or vitae. Please include undergraduate GPA scores and [GRE or GMAT] (and if applicable, TOEFL or IELTS) test scores in your resume or vitae. Please also include information about your computer programming skills (Python, R, JavaScripts, C++/ Algorithms, AWS, Mongo DB, etc.) and experience (beginner, medium, advanced, etc.). In addition, what knowledge, skills, job-related traits and abilities you may have?
One or two letters of recommendation (minimum one letter is required);
One digital portfolio document that describes the technical products YOU have created, such as class projects, GitHub websites, videos, personal or project websites, dashboards, software development, programming profile, web designing, and apps. Note: A digital portfolio is not a resume or an autobiography: only focus on your work samples. Only include your best, most professional examples. Include recent work if possible. A digital portfolio can be a PDF document or a web link to your portfolio webpage;
Copies of transcripts from all colleges and universities attended. These do not need to be sent directly from the college or university - scanned photocopies and digital copies are acceptable. Note: This is in addition to the transcripts that you submit to Graduate Admissions;
English language scores (TOEFL, IELTS, or PTE). Photocopies and digital copies are acceptable. Note: This is in addition to the scores that you submit to Graduate Admissions Office;
A GRE or GMAT score is required for applicants with an undergraduate GPA of below 3.2 or with a degree in a non-quantitative field, so that the applicants can demonstrate the requisite quantitative knowledge. Photocopies and digital copies are acceptable. Note: This is in addition to the scores that you submit to Graduate Admissions Office.

Programs

Big Data Analytics, M.S.