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Empowering you to transform data into insight to achieve business goals.

There’s a digital revolution taking place at this very moment. Harnessing the power of data, innovation, and collaboration, businesses are thinking bigger and progressing further. In a world where data is king, professionals skilled in data management and the practical application of technologies like machine learning are in high demand. Effectively analyzing big data helps businesses become better, smarter, and faster – which is why experts in data analysis are urgently required. Looking ahead, the need for data analytics experts will only surge higher and demand for analysts far exceeds the number of qualified professionals out there.

With courses focused on advanced analytics and data operations, you’ll learn how to translate data into a usable asset. Our Master’s of Science in Data Analytics will prepare you for a career in a technology-driven business environment — you’ll delve deep into Python programming, advanced statistical analysis, and data mining and warehousing. Clark will prepare you to lead your organization to better business decisions and outcomes with confidence and skill by giving you the tools to find the story behind vast amounts of data.

International Students

Candidates with science, technology, engineering, and mathematics (STEM) degrees are sought after across most major industries in the United States. When you graduate with a STEM-designated degree such as the Master of Science in Information Technology, you may be eligible to remain in this country for up to 36 months on Optional Practical Training (OPT).

Why a Master’s in Data Analytics at Clark University

  • Flexible online format with access to a robust portfolio of electives, allowing you to construct an experience that drives your own individual career aspirations.
  • Distinctive practitioner-scholar instructor model brings pragmatic real-world expertise to life in the classroom.
  • Suited to fit the needs of the modern workforce, with a curriculum that fosters both technical and ‘soft’ skills, like storytelling with data.
  • Develops system architects to prepare data for advanced analytics.
  • Longstanding history of close collaboration with local and regional organizations, ensuring research, internship, and employment opportunities.
  • Highly ranked institution with robust experience in technically oriented programs and quantitative methods.
Dean Cascione

The 4th Industrial Revolution is Upon Us

Dean Cascione dives into data to give students the skills needed to help businesses as they digitally transform through automation, artificial intelligence, machine learning, and rapid technological innovation.

Data Analytics provide enterprises with valuable business, operational, and security intelligence to uncover trends, expose anomalies, foster continuous improvement of business-critical systems, and ultimately gain a competitive advantage.

The Essentials

Program Overview

Designed for flexibility with your busy schedule, our program can be completed on a part-time basis either online or on campus. Students studying full-time can earn their degree in a year.

Incoming students with a strong math or programming background (i.e., candidates holding a B.S. in Computer Science) may waive up to 2 required courses and replace them with two other course options.

We also recognize the valuable experience and perspectives that working professionals bring to the class. If you are a student with three or more years in a professional position or hold an industry standard certification, you can apply for the Prior Experiential Credit.

Up to two course waivers may be possible after admission to the degree program, enabling you to complete your degree more quickly and cost effectively. (An administrative fee is applied if the prior experiential credit is approved).

  • Driving business growth through the use of data and advanced analytics
  • Leading strategic projects to create opportunity for data-driven decision-making
  • Investigating and diagnosing complex data interaction issues
  • Data warehouse design and optimization
  • Architect analytics solutions to find hidden opportunities and gain competitive advantage
  • Applied Machine Learning
  • Data Visualization
  • Data Mining
  • Data Warehouse and Applied SQL


10 course units

  • 9 core courses, including a Capstone project
  • 1 elective

Course Catalog