Data Analytics Major (B.S.)

The Data Analytics major prepares students to harness data for strategic decision-making in modern organizations. Students learn to apply analytical techniques to real-world business challenges, integrating skills in data management, statistical analysis, and predictive modeling with core business knowledge in areas such as finance, marketing, operations, and management. The major emphasizes the use of data to improve performance, identify opportunities, and guide strategic planning. As businesses increasingly rely on data to drive innovation and efficiency, data analytics has become a vital and rapidly evolving field. This interdisciplinary program combines quantitative rigor with practical business insight, equipping graduates with the tools to lead data-informed initiatives across a wide range of industries.

The major also provides a pathway for students pursuing the 3+1 program for the Master of Science in Data Analytics degree (MSDA). Students planning to enroll in the 3+1 program must take the graduate-level course options during their senior year, after acceptance into the program. Please work closely with your 3+1 advisor.

(Please note that the 3+1 program for the MSDA will not be offered until the 2027-28 academic year. The graduate-level courses are listed below strictly for planning and advising purposes.)

Major Requirements

69-74 credits

Mathematics and Computer Science Core (20 credits)

Complete the following to prepare for upper-level mathematics and computer science courses.

CSCI-1040Computer Science I: Intro to Comp Sci

4 credits

CSCI-2025Data Manipulation and Visualization

4 credits

MATH-1075Single Variable Calculus

4 credits

MATH-2025Multiple Regression Analysis

4 credits

MATH-2080Introduction to Proofs and Discrete Math

4 credits

Students who place out of MATH-1075 Single Variable Calculus must take MATH-2075 Multivariable Calculus instead. In this event, MATH-2075 may still count toward the Advanced Electives category.

Business Core (14 credits)

Complete the following to prepare for upper-level business courses.

ACCT-2001Financial Accounting

4 credits

ACCT-2002Managerial Accounting

4 credits

BUSN-1250Business Computer Applications

2 credits

ECON-2000Principles of Economics

4 credits

Data Analytics Core (14 credits)

Complete the following data analysis core curriculum track.  The 5000-level options are open only to students admitted into the 3+1 program for the MSDA degree.

ACCT-3235Data Analytics

4 credits

-
or

DATA-5235Introduction to Business Analytics

4 credits

-
 

BUSN-4080Project Management

4 credits

-
or

DATA-5080Project Management

4 credits

-
 

MATH-4002Introduction to Data Science

4 credits

-
or

DATA-5002Introduction to Data Science

4 credits

-
 

CSCI-2020Applied Databases

2 credits

Students planning to complete the 3+1 program for the Master of Science in Data Analytics must complete the 5000-level options above during their senior year. These students should consult with their advisor before registering. 

Decision Sciences (4 credits)

Complete at least one of the following courses. Students intending to complete the 3+1 for the MSDA should consult with their advisor before registering.

BUSN-3000Management Science

4 credits

-
or

DATA-5000Management Science

4 credits

-
 

BUSN-4050Princ of Productions & Operations Mngmnt

4 credits

Students enrolled in the 3+1 program must take the 5000-level options above during their senior year.

Advanced Electives (16 credits)

Complete at least four courses (16 credits) from the courses listed below. At least one of these courses must have a BUSN, FINC, or MKTG prefix and at least one must have a MATH or CSCI prefix and be at the 3000-level or higher.

BUSN-3250Cybersecurity for Business

4 credits

CSCI-2040Computer Science II: Data Structures

4 credits

CSCI-3040Design and Analysis of Algorithms

4 credits

CSCI-4055Numerical Computation

4 credits

ENVS-3051Intro to Geographic Info System (GIS)

4 credits

FINC-3030Principles of Finance

4 credits

FINC-4032Investment Theory and Practice

4 credits

MATH-2075Multivariable Calculus

4 credits

MATH-3025Probability and Mathematical Statistics

4 credits

MATH-3050Differential Equations

4 credits

MATH-3060Linear Algebra

4 credits

MATH-4025Statistical Machine Learning

4 credits

MATH-4050Real Analysis

4 credits

MATH-4TD9Special Topics in Data Analytics

1-4 credits

The Special Topics course above is distinct from MATH and CSCI Special Topics courses.

Capstone (1-4 credits)

Complete at least one of the following courses. Students intending to complete the 3+1 Data Analytics Master’s program should take DATA-6990 or consult with their advisor for further guidance.

BUSN-4990Business & Accnting Capstone: Sr Seminar

4 credits

MATH-4990Math-Physics-CS Capstone

1 credit

Outcomes

Upon successful completion of this major, students will have be able to:

  1. Apply fundamental statistical and mathematical techniques to clean, explore, and summarize data (assessed by MAPS);
  2. Construct, evaluate, and interpret statistical models (assessed by MAPS);
  3. Demonstrate the ability to communicate effectively both to stakeholders and as a member of a team (assessed by BUACC); and
  4. Carry out analytical problem-solving through the use of appropriate business-oriented resources for decision making in the organizational context (assessed by BUACC).

While this major will be housed within the Math and Physical Sciences department, it is a partnership between MAPS and Business. The responsibility for assessing the learning outcomes will be shared by the two departments.