Oct 03, 2022  
2017-2018 Catalog and Handbook 
    
2017-2018 Catalog and Handbook [ARCHIVED CATALOG]

Master of Science in Data Analytics


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Academic Director: Arthur O’Connor, PhD
CUNY School of Professional Studies
101 West 31st Street, 7th Floor
New York, NY 10001
Email Contact: dataanalytics@sps.cuny.edu

Effective Spring 2018 the M.S in Data Analytics will become the M.S in Data Science. To view the curriculum changes, click here.   

The Program

The online MS in Data Analytics prepares graduates to make sense of real-world phenomena and everyday activities by synthesizing and mining big data with the intention of uncovering patterns, relationships, and trends. Big data has emerged as the driving force behind critical business decisions. Advances in our ability to collect, store, and process different kinds of data from traditionally unconnected sources enables us to answer complex, data-driven questions in ways that have never been possible before.

Data analytics combines information management, systems thinking, quantitative methods, data modeling, data warehousing, and data mining to produce visualizations and other business intelligence models that help organizational leaders predict and evaluate best practices. For example:

  • Businesses can predict future sales results by combining their customers’ preference profiles with website click-stream data, social network interactions, and location data.
  • Police and fire departments collaborate with emergency managers and homeland security to develop more accurate models of automotive and pedestrian traffic by using GPS data from cars, buses, taxis, and mobile phones.
  • Emergency room physicians are able to reduce time to initial treatment and, as a result, patient mortality, by fusing aggregate patient histories with the results of up to the minute lab tests.

Admissions Criteria

In addition to the admission criteria for graduate degree programs, applicants must have earned a bachelor’s degree in Computer Science, Information Systems, or another STEM field from an accredited institution. A degree in a business-related discipline will be considered on a case by case basis depending on the nature of an applicant’s coursework.

Applicants must have the ability to program in a high-level computer language (e.g., Java, C++, Python). Applicants must also have a GPA of 3.0 or better. An admissions interview is required. For more information call 212.652.2869.

Curriculum

While the foundational courses lay out four core areas in data analytics (systems, computation, quantitative methods, and data management), the curriculum includes a breadth of cutting edge electives such as business analytics and data mining, web analytics, energy and transportation systems that provide students with options for applying analytic and informatics techniques to a host of issues that that impact the economy and our world.

Program Requirements


36 credits are required to complete the Master’s Degree in Data Analytics. Of these, 27 credits must come from the core Data Analytics requirements. The remaining nine credits are electives. For the urban sustainability track, all nine of the elective credits must be in the track.

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