Online Master's Degree in Data Analytics (M.S.)

Program Description

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:

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 for current job openings in data science and data analytics.

Admission Criteria

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:

  1. 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;
  2. Linear algebra including basic matrix manipulation, dot and cross products, inverse matrices, eigenvalues, representing problems as matrices, and solving small systems of linear equations;
  3. Programming in a high level language such as Python, Java, JavaScript, C++, C, Ruby, or SAS (2+ years). Applicants must be able to write working code from scratch;
  4. 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,
  5. 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:

  1. 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,
  2. Completion of a mandatory challenge exam that will assess current skill and knowledge in these areas.

If you need to refresh or develop your skills, we offer two options: 

  1. 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
  2. Undergraduate Courses: If you are new to this level of math and data programming, or need more in-depth preparation, we offer up to six fully-online undergraduate courses:

IS 210 Software Application Programming I
IS 211 Software Application Programming II 
IS 360 Data Acquisition and Management 
IS 361 Database Architecture and Programming
MATH 215 Introduction to Statistics 
MATH 315 Discrete Mathematics and Linear Algebra

For the undergraduate courses, you must enroll as a non-matriculated student.  Click here to download the non-matric application form.  Please return your completed application form to rokshana.ali@mail.cuny.eduIf you have questions, please contact Rokshana Ali, MSDA Program Specialist, at or 646.664.8516.

*International students may enroll in fully online degree programs. However, our online programs do not qualify for student visas.

Application Deadlines


For more information about the program, contact or 212.652.2869.