Choose search location

Requirements

The Master of Science in Data Science and Business Analytics (MSDSBA) curriculum is structured to be completed in a single year (fall, spring/summer, and winter) or a two-year program for part-time students, with a total of 30 credit hours required. The program offers three majors: advanced analytics, data computing, and data-driven business.

Trained by world-class faculty under the stewardship of a strong advisory board, students will learn identification and framing of problems; acquisition, management, and utilization of large and fast-moving streams of data; creation, analysis, solution, and interpretation of mathematical models using appropriate methodology; and the integration of these interdisciplinary skills to enable graduates to successfully develop and execute data science and business analytics projects.

The interdisciplinary core includes nine hours of coursework across business, computer science and industrial systems engineering. On top of this integrated breadth of study covering the core areas of data science and business analytics, each student has nine hours of major-specialized courses to give them depth in data computing, business or analytics areas of specialization. Each student's six credits of elective choices can be personalized to support their individual career goals.

The final piece of the curriculum is a six-credit applied analytics practicum, in which teams of students will work with companies and organizations on real analytics problems.

Base curriculum: All majors

  • Data Science Analytics (3 credits)
  • Data Science Strategy & Leadership (3 credits)
  • Computing Platforms for Data Science (3 credits)
  • Choose one of three specialization majors, each consisting of:
    • Three core courses (9 credits)
    • Two elective courses (6 credits)
  • Practicum (6 credits)

Each student's course choices must satisfy the requirements of at least one of the three defined majors below.

Majors

Advanced Analytics

The Advanced Analytics major provides students with greater knowledge and understanding of the quantitative methodology of descriptive, predictive, and prescriptive analytics: how to select, build, solve and analyze models using methodologies such as parametric and non-parametric statistics, regression, forecasting, data mining, machine learning, optimization, stochastics, and simulation. Advanced Analytics curriculum.

Data Computing

The Data Computing major provides students with a deeper understanding of the practice of dealing with so-called Big Data: how to acquire, preprocess, store, manage, analyze, and visualize data arriving at high volume, velocity and variety. Data Computing curriculum.

Data-Driven Business

The Data-Driven Business major provides students with a deeper understanding of the practice of using analytics in business and industry: how to understand, frame, and solve problems in marketing, operations, finance, management of information technology, human resources, and accounting to develop and execute analytics projects within businesses. Data-Driven Business curriculum.

Elective courses

The program offers an extensive list of elective courses. 

Capstone experience

In the final spring/summer semester, each student will complete a six-credit applied practicum. Students may pursue an applied analytics internship, working on a significant analytics project at a company or organization site, or they may choose to work in a cross-disciplinary team on a significant data science and business analytics project that companies and organizations bring to campus. Such teams will consist of MSDSBA students from each major to bring each of their specializations to bear in an integrated solution. In this way, the interdisciplinary learning will be emphasized in practice as well as in the classroom.

Additional resources

In addition to learning from world leaders and cutting-edge researchers in data science and business analytics, students in the MSDSBA program will have access to a variety of specialized resources, including:

  • Academic and professional advising
  • Job placement support
  • Funding to attend a major analytics conference
  • Exposure at Wayne State's annual Big Data and Business Analytics Symposium
  • Wayne State's state-of-the-art high-performance computing infrastructure for massive-scale analytics
  • Free cloud computing resources
  • Free and discounted analytics, engineering, and productivity software

How to apply

Admission to the Master of Science in Data Science and Business Analytics program is highly selective. Exceptional students with a strong interest in data sciences and business analytics, with a high level of ability as demonstrated by past performance in appropriate coursework, standardized testing and/or by workplace experience.

All applicants are expected to have basic background in mathematics (in particular probability and statistics) and computing (at least one college-level course or equivalent knowledge in computer programming using a high-level language like C, C++, Java, Python, R, FORTRAN, etc.), as well as a bachelor's degree or equivalent. Applicants must submit either GRE or GMAT scores, a professional resume, a Statement of Purpose, and contact information for two people who will submit letters of recommendation. English Language Proficiency passing test scores (See Graduate School Minimum Test Scores) are required for international applicants.

Applicants who do not have sufficient background in mathematics and computing may still be admitted, with the expectation that they either learn the necessary background material on their own before arriving or take one or more preparatory courses from Wayne State University such as:

  • DSE 5070: Introduction to Data Computing and Programming

Other courses from online platforms such as Coursera and EdX may be allowed as substitutes on a conditional basis.

Application

Begin the application process today! Select which program you want to apply for: the M.S. in Business or M.S. in Engineering. The M.S. programs have three concentrations: Data-Driven Business (based in the Mike Ilitch School of Business), Advanced Analytics (based in the College of Engineering) and Data Computing (based in the College of Engineering). Make sure that you select the appropriate concentration/track when you apply.