- Offered as:
Data analytics tools and techniques are used by many different industries to create, manage, and explore big datasets, extract information and develop predictive models, and make better decisions. In recent years, there has been an explosion in demand for skilled data analysts.
Core data skills will enable you to work as a data analyst in diverse employment sectors. In addition to strong data analytics skills, you will develop domain knowledge needed to translate raw data into appropriate industry applications. You’ll customize your degree with one of nine specialization tracks:
- Actuarial Science
- Agricultural and Environmental Systems
- Data Visualization
- Life Sciences
- Physical Sciences
- Social Sciences
- Strengths of the program
You will have extensive “hands-on” opportunities to work with real industry and academic datasets that will prepare you for well-paid job opportunities.
Specializations allow you to connect your education to your interests and career goals.
WSU is one of only two research universities in the U.S. to offer an undergraduate degree specifically designed to prepare students for leadership in data analytics.
The WSU program is truly interdisciplinary. Faculty and researchers span seven colleges and numerous academic departments and schools.
- Requirements and core courses
The data analytics curriculum guides you through development of strong technical skills, builds your working knowledge of an application area, and fosters vital workplace communication skills and the ability to work in teams.
The WSU data analytics degree requires:
- Core courses in mathematics, statistics, computer science, and philosophy
- Completion of one of nine specialization tracks
- Satisfaction of WSU UCORE general education requirements
- Electives sufficient to complete a minimum of 120 credits overall
Core courses for all students include:
- Survey course of the field of data analytics (freshman year)
- 10 credits in calculus and linear algebra
- 11 credits in lower-division fundamental computer science
- 9 credits in upper-division computer science with a data science focus
- 15 credits in statistics
- 3 credits in philosophy, addressing the ethics of data analytics
- Project-focused capstone course (senior year)
Courses and requirements for specialization tracks vary. Visit data-analytics.wsu.edu for details.
- Scholarships and financial aid
Washington State University awards millions of dollars in financial aid and scholarships to students every year based on financial need, academic merit, or a combination of the two.
To get all the financial help WSU can provide:
- Complete the University's general scholarship application so you can be eligible for scholarship consideration.
- Complete the FAFSA (Free Application for Federal Student Aid) so WSU can consider you for aid (scholarships, grants, loans, etc.) based on financial need.
- Suggested preparation for incoming students
- Four years of high school mathematics (through at least pre-calculus)
- Familiarity with programming
- Interest in computers and software applications
You'll probably do well in data analytics if you:
- Enjoy exploring data and probability across a range of interests like sports, politics, health, or money
- Have an aptitude for analytical thinking, including success in math or science classes
- Have the ability and desire to stick with a difficult problem through its ultimate resolution
Data analytics is currently the most in demand of all technical fields, with starting salaries in six figures for some application areas.
Core data skills acquired in the degree enable you to work as a data analyst in diverse employment sectors, including manufacturing, e-commerce, transportation, retail, health care, government, insurance, finance, education, environmental management, and more.
Your degree specialization will facilitate your entry into companies and industries that need data analysts:
Risk assessment; asset and investment management
Agricultural and Environmental Systems
Forest management; precision agriculture; geographic information systems
Management consulting; data architecture; market research; supply chain management
Software engineering; data science; database management
Forecasting; auction design; e-commerce optimization
Bioinformatics; biomedical research and development
Cheminformatics; computational chemistry; product/process development
Adaptive Learning; policy research; psychometrics; program evaluation
Read more about the expected need for data analytics in the 2016 U.S. Federal Big Data Research and Development Strategic Plan.