Apr 01, 2023  
2022-2023 Graduate Catalog 

Master of Science in Data Analytics

The M.S. program in data analytics provides students the advanced knowledge and skills to analyze organizational data. The use of analytics is accelerating due to technological advancements, exponential growth in data, and increasingly sophisticated application by organizations. Analytics is embedded in all industries, business functions, and employee workflows. The program prepares students for data-driven leadership and problem solving. Graduates of the M.S. in data analytics will be data-driven thinkers to approach business decision-making more rigorously and confidently, while effectively communicating data findings, interpreting complex data, and guiding their organizations in making more informed and actionable strategic decisions.

The program is in an online format for a large population of potential graduate students who cannot commit to either a full-time or location-based program to obtain the advanced degree. The program consists of two phases. Phase One (6 semester hours) is designed to address deficiencies in undergraduate course work considered to be prerequisite for the Phase Two (30 semester hours) graduate course work. Students with significant undergraduate course work in business may be waived from some, or all, of the Phase One requirements. Exemption exams are also available to waive Phase One requirements. There is no charge for the exam, however, a student may only attempt each exam once. Phase Two consists of 10 courses to ensure an in-depth study in data analytics.

Check departmental information for additional requirements.

Learning Outcomes

Master of Science in Data Analytics Program Competencies and Learning Objectives 

Graduates from the NIU Department of Operations Management and Information Systems’ Master of Science in Data Analytics program will fulfill the following program competencies and learning objectives.

1. Data-Driven Decision-Making: to provide the student with the knowledge to make business decisions based on insights derived from data.

  • The student can explain how analyzing data can improve business decision-making.
  • The student can evaluate business processes using data.

2. Data Analytics Lifecycle: to provide the student with the skills to complete data analytics projects.

  • The student can contrast different forms of analytics and the methods used in each.
  • The student can utilize analytical tools and software.
  • The student can collect and prepare data for statistical analysis.
  • The student can build complex analytical models.
  • The student can apply project management concepts and tools to data analytics projects.

3. Communication: To provide the student with the ability to communicate the results of a data analysis.

  • The student can effectively present results using data visualization tools.
  • The student can explain complex results from data analysis to business clients using practical and simple business terms that can be understood by non-technical audiences.


Admission to the Master of Science in data analytics program is competitive. At minimum, applicants must meet the admission requirements of the NIU Graduate School and demonstrate that they possess the following minimum qualifications: 

For applicants with a baccalaureate or higher degree from an accredited U.S. college or university:

  • Strong record of academic achievement demonstrated by cumulative GPA.
  • The GMAT/GRE is not required but may be submitted to supplement the academic record if GPA does not fully demonstrate academic ability.

For International applicants without a baccalaureate or higher degree from a U.S. college or university, GRE or GMAT is required for admission:

  • Strong record of academic potential demonstrated by GMAT or GRE score.
  • Official IELTS (minimum 6.5 overall) or TOEFL (minimum 80) score received directly from the testing agency.

For NIU University Honors graduates:

NIU University Honors students who graduate with a B.A. or B.S. are guaranteed admission into the Master of Science in Data Analytics (MSDA) program as space permits.

Phase One (6)

The Phase One foundations consist of three 2-semester-hour courses. Phase One foundation courses will be required in students’ program of study unless they have earned a C or better in corresponding undergraduate courses or a B or better in equivalent graduate courses elsewhere, or have passed the first and only attempt of Phase One exemption examination. The department program adviser will determine which Phase One courses will be included in students’ program of courses. Credits earned in Phase One will not count toward the Phase Two requirements. Phase One consists of the following courses:

Phase Two (30)

Total hours (30-36)