This guide is for information and resources on data and data literacy.
Data is defined as "a raw form of information that may be difficult to interpret, includes numbers, letters, words, images, or any other material that contains knowledge."
Dziak, Mark. “Data Literacy.” Salem Press Encyclopedia, 2021.
Data Literacy is the ability to understand data in context and effectively use data to form and support institutional goals. For faculty and instructional staff at ACC, it is to understand how to access, read, interpret, discuss, analyze, and use data-driven decisions to improve programs and student outcomes, and use data to inform their practice as relevant to their role.
Data Engagement for Student Success, 2024.
Data analysis is the statistical and logical technique used to interpret and evaluate data. It includes collecting, formatting, cleaning, and processing data as well as analysis and interpretation.
“Data literacy explained: Definition, importance, examples, and more.” Tableau, 2024.
Data visualization is the graphical representation of information in different forms, such as charts, graphs, maps, etc.
“Data literacy explained: Definition, importance, examples, and more.” Tableau, 2024.
Data management is the entire process of collecting, vetting, and storing data.
“Data literacy explained: Definition, importance, examples, and more.” Tableau, 2024.
If you want to build dashboards or complex data analysis programs, you need to understand and use programming languages. Some of the best for data work include Python, R, and SQL.
“Data literacy explained: Definition, importance, examples, and more.” Tableau, 2024.