Data science studies how to use data to solve problems and answer research questions. It constitutes all parts of a data-intensive workflow, from the beginning (e.g., data collection, data preparation), through the middle (e.g., data mining, supervised/unsupervised machine learning) to the end (e.g., presenting insights and/or deploying a software system). It helps to think about data science as science, meaning it uses the scientific method we are all familiar with but with a focus on data.
See the current Gonzaga Catalog for more.
