Data Analytics

Located within the College of Arts and Sciences, the Bachelor of Science in Data Analytics degree is interdisciplinary, with classes in mathematics, statistics and computer science. Students may choose from three tracks: actuarial science, business or data visualization.

Data analytics applies fundamental scientific principles to the analysis of large, complex data sets, which are important tools in the world of business. Many companies, nonprofits and government agencies collect data to evaluate past performance and predict future trends. They employ data scientists to extract important details from data and help make decisions to strengthen the business. View career information.

Our primary goal is to train our students to be responsible data citizens and serve as the conduit between the theory (computing, mathematics and statistics) and the field (domain that the data arises from), understanding the principles of both. Graduates of the program will have an ability to analyze and communicate various kinds and types of data from start to finish, using techniques that are: theoretically valid, practically feasible and relevant and ethically and legally viable.

Given this over-arching goal we would like to emphasize the following program education objectives (PEO).

With a Bachelor of Science in Data Analytics from WSU Vancouver, you can:

  1. Understand data and its analysis in theory (using computing, mathematical and statistical principles), in practice (computing methods, software, analysis, coding) throughout the data lifecycle.
  2. Understand the context of the data, domain it comes from, type of data, questions of interest and apply methods to solve them.
  3. Recognize professional responsibilities as data analysts: understand ethical and legal responsibilities regarding the data one has access to; understand the concepts of security and privacy of data; have confidence in these principles to articulate misuse and abuse of data.
  4. Effectively communicate (verbally, written and visual) in a variety of professional contexts, understanding and appreciating their audience.
  5. Function effectively as a member or leader of a team engaged in activities appropriate to data analytics.