Online Master's Degree in Data Analytics (M.S.)
The Online Master's Degree in Data Analytics (M.S.) prepares graduates to make sense of real-world phenomena and everyday activities by mining and visualizing data. Big data has emerged as the driving force behind smarter business decisions and intelligent machines.
Data analytics combines data programming, quantitative methods, data modeling, data mining, and machine learning to help organizations predict future events and evaluate past performance. 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.
Careers in Data Analytics
Graduates of the Online Master's Degree in Data Analytics are prepared for a variety positions such as Data Scientist, Business Intelligence Analyst, Data Analyst, Data Mining Engineer, and Data Warehousing Manager. See Indeed.com for current job openings in data science and data analytics.
As an interdisciplinary field, we welcome applicants from diverse professional backgrounds. However, because the M.S. in Data Analytics is a highly quantitative and technical major as compared with MBA-like programs, acceptance requires applicants to demonstrate current skills in:
- Statistics and probability including descriptive statistics, skewness/kurtosis, histograms, statistical error, correlation, single variable linear regression analysis, significance testing, probability distributions, and basic probability modeling;
- Linear algebra including basic matrix manipulation, dot and cross products, inverse matrices, eigenvalues, representing problems as matrices, and solving small systems of linear equations;
- Relational databases including connecting to and manipulating data, working with tables, joins, basic relational algebra, and SQL queries. Two or more years of experience with Microsoft Access can be substituted if the applicant is able to perform the same operations without using Access’s graphical interface; and,
- Analytical thinking including the ability to translate real-world phenomena into quantitative representations and, conversely, the ability to interpret quantitative representations with practical explanations.
Skills in these areas will be assessed in two ways:
- Completion of credit bearing coursework with a grade of B or better from an accredited college or university OR 2+ years of relevant experience on a resume; and,
- Completion of a mandatory challenge exam that will assess current skill and knowledge in these areas.
If you need to refresh your skills, we offer the following Bridge Program:
If you have completed credit-bearing courses in the above areas or have used these skills at work but are no longer proficient, we offer two seven-week bridge courses in quantitative methods and data programming. These bridge courses are intended to refresh knowledge and skills, but are not for individuals who are learning these topics for the first time. See http://sps.cuny.edu/admissions/msda_workshops.
If you have questions, please contact Rokshana Ali, MSDA Program Specialist, at firstname.lastname@example.org or 646.344.7302.
*International students may enroll in fully online degree programs. However, our online programs do not qualify for student visas.
- Applications for Spring 2016 due by December 15, 2015 — Apply Now
For more information about the program, contact email@example.com or 212.652.2869.