Ohio State nav bar

Business Analytics Specialization

Specialization Educational Objectives

In addition to the core objectives, a student graduating with a Bachelor of Science degree with a major in Data Analytics with a specialization in Business Analytics:

  • will demonstrate an understanding of how research and data analytics are done in business.
  • will demonstrate proficiency at designing and implementing analyses to carry out a firm’s business objectives.
  • can identify and assess ethical issues surrounding business decisions.

Degree Planning Resources

These documents outline the prerequisite structure within the core curriculum and demonstrate how students flow through the required courses for the Data Analytics major with a specialization in Business Analytics. They should be used as guides only. Semester course offerings are subject to change.

Since AU 2022 with NEW GE (GEN)

Before AU 2022 with LEGACY GE (GEL)


Specialization Requirements

All students specializing in Business Analytics must complete the following specialization requirements:

Required General Education Courses

  • ECON 2001.01 (or .02 or .03): Principles of Microeconomics
  • ECON 2002.01 (or .02 or .03): Principles of Macroeconomics

As noted on the GE advising page, Econ 2001.01 and 2002.01 can be used to fulfill the GE requirements in the Social Sciences category.

Business Industry Immersion Program

  • BUSADM 3630.05: Introduction to Business Analytics: Defining and Applying "Big Data"
  • BUSADM 3632.05: Design and Development of Business Analytics Solutions

A pre-requisite for enrolling in BUSADM 3630.05 and 3632.05 is enrollment in the Fisher College of Business Industry Immersion Program.  Please be aware that the eligibility requirements for enrolling in the program include a cumulative GPA of at least 3.0.

The required courses BUSADM 3630.05 and 3632.05 serve as the capstone experience for the Business Analytics specialization. These courses represent a contiguous two semester program in the Business Analytics Industry Immersion Program cluster that will introduce the students to business analytics (Autumn) and then allow them to work in small teams on projects provided by the class sponsors (Spring). The Autumn semester will utilize faculty from the Fisher College of Business combined with external corporate speakers/presenters. Current sponsoring companies for this two semester program include JP Morgan Chase, Scotts Miracle Gro, Lane Bryant, Saama, and Cardinal Health. Sponsors are continually added to the program, and as a result, each session will vary in speaker content and student projects.  Students will work on two separate sponsor projects in the spring and will be expected to present to representatives from the sponsoring companies.

Business Electives

In addition to the courses listed above, students in the Business Analytics specialization must take an additional 9 credit hours of coursework from the electives listed below.  Courses are grouped to show possible focus areas but students may select any combination of courses (having met appropriate pre-requisites) to meet the 9 credit hours requirement.

Electives: Finance Focus

Electives: Accounting and Management Information Systems Focus

Electives: Customer Insights Focus

  • BUSML 3150: Foundations of Marketing (3 cr hrs)
  • BUSML 3250: Principles of Marketing (3 cr hrs)
  • BUSML 4202: Marketing Research (3 cr hrs)
  • BUSML 4210: Advanced Market Research (1.5 cr hrs)
  • BUSML 4211: Market Analysis, Development & Forecasting (1.5 cr hrs)
  • BUSML 4212: Customer Relationship Management (1.5 cr hrs)

Electives: Operations & Logistics Focus

  • BUSOBA 3230: Introduction to Operations Management: Improving Competitiveness in Organizations (3 cr hrs)
  • BUSOBA 4250: Six Sigma Principles (3 cr hrs)
  • BUSOBA 4251: Six Sigma Projects (3 cr hrs)
  • BUSML 3380: Logistics Management (1.5 cr hrs)
  • BUSML 4382: Logistics Analytics (3 cr hrs)
  • BUSML 4386: Logistics Technology and Application (1.5 cr hrs)

[pdf] - Some links on this page are to .pdf files. If you need these files in a more accessible format, please contact data-analytics@osu.edu.