Bachelor in Data Analytics
Data analytics is a rapidly growing profession across a wide range of fields, including finance, healthcare, insurance, biomedical research, computer science, marketing, and many other areas. Experts in data analytics have quickly become valued for their ability to process large amounts of data, detect significant trends, and make insights that drive important decisions.
About the Major
This major combines study in math and computer science with a firm foundation in the liberal arts. In her TED Talk on challenges in interpreting big data, data analyst Susan Etlinger said: "What we need to do instead is spend a little bit more time on things like the humanities and sociology, and the social sciences, rhetoric, philosophy, ethics, because they give us context that is so important for big data, and because they help us become better critical thinkers."
OWU's program requires students to be strong in quantitative methodology, and it helps you develop the skills to use data to explore and make connections in larger social, political, and economic contexts. In addition to foundational studies in mathematics and computer science, you also will take courses in:
- The social, ethical, and cultural impacts of big data in our lives
- Data visualization, where you'll learn how to communicate effectively with data
- Science writing
- And data-related issues in the sciences, humanities, and arts.
Since careers in data analytics span many industries, this can be a valuable second major. Ohio Wesleyan also offers minors in data analytics and data and society.
A major in Data Analytics should have a combination of technical knowledge, disciplinary-specific skills
and social and political knowledge that enables them to:
1. Technical Knowledge
- a. Understand how data is stored/processed/used
- b. Analyze data using a variety of statistical techniques
- c. Manipulate data using a variety of programming techniques
- d. Recognize abstract organizations and constructs of data
- e. Visualize and communicate data for multiple audiences
- f. Work with real, large and complex datasets
2. Discipline Specific Applications
- a. Articulate problems specific to a discipline
- b. Represent a problem in a manner conducive to solution
- c. Frame questions and represent them symbolically
- d. Communicate findings to appropriate audiences
3. Social, Cultural, and Ethical Impacts
- a. Assess the impact of big data on existing societal institutions and norms
- b. Assess the impact of specific research on individuals and communities
- c. Assess the impact of research design on the scope and applicability of the resulting conclusions
- d. Recognize ethical dilemmas and assess implications of research with big data
The major in Data Analytics will consist of 13 courses.
- DATA 100 1 Introduction to Data Analytics
- CS 110 Introduction to Computer Science and Programming
- MATH 110 Calculus I
- MATH 230 Applied Statistics
- CS 210 Intermediate Computer Science and Data Structures
- CS 300 1: Databases and Machine Learning for Data Analytics
- ENG 312 Writing for the Sciences
- DATA 300 1: Social, Ethical, and Cultural Impact of Big Data
- DATA 300 2: Data Visualization and Presentation
- DATA 300 3: Methods in Data Analytics
- DATA 400 1: Capstone in Data Analytics
- Two cognates from any one discipline below or other courses as approved by the director or steering committee of the major.
Politics and Government
- PG 279 and one of the following:
- PG 261, PG 344, PG 347, PG 363 or PG 359
- ACCT 280
- BUS 462 or BUS 465
Every data analytics major works under the guidance of a faculty member to complete a capstone research project. Students take the classroom theory and methods they've learned and put them into practice in actual challenges faced in society.
In the 10-week intensive Summer Science Research Program, students work as paid researchers with a faculty mentor on a topic of mutual interest.
Program taught in: