The Master of Science in Data Analytics program provides you with the skills to be an effective data professional in a rapidly growing field.

Upon completion, you will be able to identify, acquire, manage, present, analyze and interpret large amounts of data in a variety of organizational settings. You'll learn how to turn big data into smart data, improve operations efficiency, and understand the factors that turn consumers into customers.

Online or on-site, the data analytics program offers close faculty and student interaction, with core courses ensuring that you acquire key critical skills from industry experts. In addition, the program offers a range of elective courses in various areas of data analytics from which you can build additional levels of proficiency and expertise while rounding out your education.

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Clarkson's MS in Data Analytics

Data Analytics Curriculum

The 36-credit MS in Data Analytics degree program consists of six 3-credit core graduate courses, four 3-credit graduate elective courses, and one 6-credit capstone course based on a sponsored project or internship. Full-time, residential students generally complete the program in three semesters. Students can complete the program at the Potsdam campus or 100% online. Additionally, online students can build part-time or full-time schedules that work for them. Part-time students generally finish the program in about two years.

Data Analytics Curriculum

1 in 5 CU Alumni is a  CEO, president, owner or a senior  executive of a  company
Learning Experience

The Data Analytics program is offered both online and on-site for maximum flexibility. Take courses as a residential student in a traditional, on-site classroom setting at our main campus in Potsdam, NY.  Or, keep working and earn your degree online with classes available anywhere! Online class delivery is a mix of both synchronous (students attend class online together at the same time) and asychronous (attend that week's class on your own schedule).

Online or on-site, your courses are taught by the same professors. They give you personal attention to help you learn as an individual and to prepare you for success in today’s intensely competitive market.

Student Perspective

Hear From a Student About His Experience in the Data Analytics Program

Careers in Data Analytics


Demand for data science and analytics professionals in the U.S. is quickly outgrowing the supply of such talent. The number of data science and analytics job listings is expected to increase by 364,000 openings to 2,720,000 by 2020, according to a 2017 report published by IBM. 

Career Guide

Wondering what a career in data analytics entails or how to prepare for this career? Download our guide "Considering a Career in Data Analytics?" to learn more about entering this in-demand field.

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Explore Data Career Paths

Data Science Vs. Data Analytics

Understand the key differences between data science and data analytics in order to determine which degree is right for you.

Data Analytics

Data analysts work in the entire lifecycle of data looking for action points to solve real industry problems. This means everything from gathering, managing, storing and transforming data, to analyzing and presenting it in a visually appealing and intuitive way. The information they gather can be used to make strategic decisions within their company, often improving upon the efficiency of the operation.

Data Science

While data scientists work within large data sets, the end result is more focused on technical skills, creating tools, systems and frameworks to help address theoretical situations and problems on a larger scale. Data scientists have an extensive background in statistics, computational methods and programming, enabling them to determine what approach is most appropriate for a given data set and analytical goal.

General Admission Requirements

Admission is based on your drive, academics, references, test performance and how you'll fit into the program.

An application includes:

  • Transcripts from your undergraduate institution(s).
  • GMAT/GRE scores (may not be needed for applicants with work experience, graduate degrees or other practical/applied skill sets).
  • Resume.
  • Statement of purpose.
  • Letters of recommendation.

International Students

  • English Proficiency Testing: TOEFL of 80 or higher; or IELTS of 6.5 or higher.
  • Certificate of finance to receive an I-20.

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Meet Our Data Analytics Faculty

Director Dr. Boris Jukic describes how the Data Analytics program prepares students for successful careers as data professionals. 


Data Analytics instructor Tyler Conlon talks about the big data courses he teaches and the value of gaining programming experience.


Joe Skufca, professor and chair of mathematics department

Professor Joe Skufca teaches a math class to his students on campus.


Sumona Mondal, associate professor of mathematics

Sumona Mondal speaking at the 2018 Healthy Water For New York & Beyond conference at the Beacon Institute.


Daqing Hou, professor and director of software engineering

Daqing Hou, associate professor of electrical and computer engineering, is photographed with a sensor.


Contact Us

Boris Jukic
Director of Business Analytics

Graduate Admissions

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