IS 460 - Data Visualization

(3.00 cr.)

Investigates the processing and cleaning of real-world datasets and their appropriate representation in visual form. Data resides in a multitude of databases and formats and comes in a variety of forms such as structured, semi-structured, and unstructured. Making data understandable to non-technical users requires knowledge of the best techniques for presenting data to aid in its interpretation. This course focuses on the use of data visualization coding techniques in software applications such as Tableau™, Python, and R. Students discover how to create bar charts, line charts, dual axis plots, histograms, trellis charts, pie charts, donut charts, nested pie charts, bump charts, heatmaps, spider plots, maps, and more. Prior programming experience is recommended.

Prerequisite: IS 251 or BH 251 or written permission of the department chair.
Sessions Typically Offered: Fall/Spring
Years Typically Offered: Annually

Interdisciplinary Studies: DS