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Program in Data Analytics
data-analytics.wsu.edu
Neil 103
509-335-3736
Director and Professor, N. Dasgupta (Pullman)
Data analytics is the application of powerful new methods—drawn from computer science, mathematics and statistics, and domain sciences—to collect, curate, analyze, discover and communicate knowledge from “big data.”
There has been an explosion of demand for skilled data analysts who can communicate, solve problems, and work effectively in teams. Data analytics tools and techniques are used by many different industries to create, manage, explore, and analyze large, complex datasets in order to evaluate past performance, predict future trends, and make better decisions.
Our students are trained in advanced statistical, data, and computer science skills as well as concentrated domain knowledge. This combination enables WSU graduates to effectively work in teams and easily communicate with colleagues and managers to solve problems.
The ten specialization concentrations, including the General concentration, are curricular partnerships between the College of Arts and Sciences and the Voiland College of Engineering and Architecture, Carson College of Business, College of Education, and the College of Agriculture, Human, and Natural Resource Sciences.
Students graduating with a BS in Data Analytics from WSU will be able to:
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Understand data and its analysis in theory (using computing, mathematical and statistical principles), in practice (computing methods, software, analysis, coding) throughout the data lifecycle.
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Understand the context of the data, domain it comes from, type of data, questions of interest and apply methods to solve them.
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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.
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Effectively communicate (verbally, written and visual) in a variety of professional contexts, understanding and appreciating their audience.
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Function effectively as a member or leader of a team engaged in activities appropriate to data analytics.
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