Data Analytics Degree Plan
Introduction
Data shapes decisions across healthcare, public policy, business, technology, and education. The Data Analytics program at Washington State University prepares students to turn complex information into meaningful, evidence-based insight.
Grounded in the liberal arts and powered by statistics, computing, and applied analysis, the program emphasizes critical thinking, ethical data use, and clear communication. Students learn how to analyze data and how to ask the right questions, recognize meaningful patterns, and explain their findings to complex and dynamic audiences.
Through hands-on coursework, interdisciplinary collaboration, a required internship, and a real-world capstone project, graduates leave ready to apply data analytics across industries and communities.
Admission to the Major Requirements
Students are admitted to the data analytics major and their choice concentration option upon completion of 24 semester credits with a 2.0 cumulative GPA. There is no application required for admission to the data analytics major.
Information about specific coursework required for each concentration is available at data-analytics.wsu.edu.
Lower Division
- DATA 115: Intro to Data Analytics [QUAN]
- DATA 121: Computational Calculus I or Math 171: Calculus I
- DATA/MATH 225: Linear Algebra with Modern Applications or Math 220: Linear Algebra
- DATA 219: Data Structures for DATA Analytics or CPTS 215: Data Analytics Systems & Algorithms
- DATA 122: Computational Calculus II or CPT_S/CS121: Program Design and Development C/C++ or CPT_S/CS 131: Program Design and Development Java
Upper Division
- DATA 303: Introduction to SQL, The Structured Query Language
- DATA 319: Model-based and Data-based Methods for Data Analytics or CPT_S 315: Introduction to Data Mining
- DATA 324: Data Repository Systems for Data Analytics or CPT_S 451/CS 351: Intro to Database Systems
- DATA/STAT 360: Probability & Statistics
- DATA 422: Corporate Data Analytics or CPT_S 415: Big Data
- DATA 424: Data Analytics Capstone
- DATA/STAT 435: Statistical Modeling for Data Analytics
- DATA/STAT 437: High Dimensional Data Learning and Visualization
- DATA 498: Internship
- PHIL 450: Data Analytics Ethics
Recommended/Elective (not required)
- STAT 419: Multivariate Statistics
- Math 172: Calculus II
Specialization Options
Our innovative domain knowledge Options are designed to prepare you for high-impact careers across a wide range of industries—including manufacturing, retail and e-commerce, transportation, finance, environmental management, healthcare, education, government, biotechnology, and more. These Options provide specialized skills that are in high demand, opening doors to diverse and rewarding professional opportunities.
The eleven concentration options are
- Actuarial Science
- Business
- Computation
- Data Visualization
- Economics
- Environmental Systems
- General
- Life Sciences
- Physical Sciences
- Social Sciences
- Sport Management
Note: Post baccalaureate option replaces the specialization with existing major.
Campus Options
- Pullman: All
- Everett: Actuarial Science, Business, General
- Global Campus: Business, General
- Vancouver: Actuarial Science, Business, Data Visualization, General
For more information
Why Data Analytics at WSU?
A Pioneer in Interdisciplinary Analytics
Launched in 2016, WSU’s Data Analytics program was among the first interdisciplinary undergraduate programs of its kind at a U.S. research university. That early start translates into a mature, well-integrated curriculum with deep connections across math, statistics, computer science, business, agriculture, environmental science, and the social sciences.
Eleven Specialized Concentrations
Students can customize their degree through 11 concentration areas, including Business, Data Visualization, Agricultural & Environmental Systems, Life Sciences, Physical Sciences, Social Sciences, Actuarial Science, Computation, Economics, Sports Management, and General Data Analytics. Programs are available across Pullman, Vancouver, Everett, and Global Campus, offering rare flexibility at the undergraduate level.
Real-World Experience, Built In
Every student completes a mandatory internship and an industry-supported capstone project using authentic datasets. From supply chain optimization to risk modeling, students graduate with practical experience – and professional connections – that set them apart.
Technical Rigor with Ethical Grounding
The core curriculum provides strong preparation in calculus, linear algebra, computer science, machine learning, and statistics, paired with training in ethics and responsible data use. Graduates leave prepared to analyze data thoughtfully, responsibly, and with real-world impact.