An introduction to this five module series on the competencies of data literacy in a higher education institutional environment.

An in-depth look at key types of institutional data (structured vs. unstructured, administrative vs. assessment, etc.), the sensitivity of data, and some data hot topics.

A deep dive into the reasons why institutions should prioritize data accessibility, the difference between internal and external data, and two key data assets at the University of Iowa: the Data Hub and Campus Data.

A broad overview of the reading data basics, some key statistical measures in reading data, the importance of data quality and context, how data visualizations effect reading data, and reading data for decision-making.

A quick look into the best ways to use data effectively, including the basics of the ETL process, the four main types of data analysis, tools to use in those analyses, and the importance of ethics in the use of data.

A peak into the importance of communicating data clearly by defining context and purpose, knowing your audience, creating a shared language among data producers and consumers, and shaping the narrative for action.