Abstract: When we imagine the work of a data analyst, we often picture meaningful data analysis and beautiful data visualizations. Although that is an exciting part of the job, data analysts actually spend the majority of their time acquiring, cleaning, and preparing data for analysis. This teaching case guides students through some of the most common data cleaning challenges, including handling missing data, reshaping datasets, splitting columns, and profiling data to anticipate data quality concerns. Students will practice these skills in Microsoft Power BI, a current market leader in data analytics, using real-world, publicly available data from the popular United States real-estate platform Zillow. This case would be a good addition to data analytics, data management, or data visualization classes, or in general information systems courses looking to introduce students to the vital activity of data cleaning.

Keywords: Teaching case, Data cleansing, Data literacy, Data acquisition, Data analytics

Download This Article: JISE2024v35n4pp456-460.pdf

Recommended Citation: Collier, C. A. (2024). Teaching Case: Cleaning House: A Case Teaching Data Cleaning Using Real-World Zillow Real Estate Data. Journal of Information Systems Education, 35(4), 456-460. https://doi.org/10.62273/OQXC8468