Definitions: Data is a set of values of qualitative or quantitative variables. Data is measured, collected and reported, and analyzed, whereupon it can be visualized using graphs, images, or other analysis tools. Data analysis is a process of inspecting, cleaning, transforming, visualizing, and modeling data with the goal of discovering useful information, suggesting conclusions, and supporting decision-making.

Data Analytics-Across the Curriculum Level (DA-AC) Learning Goals:

Build on the skills obtained in DA-F courses in order to use authentic disciplinary or interdisciplinary specific data analysis and visualization techniques.
Draw conclusions from data analysis and visualization to further insight into the discipline or interdiscipline.
Communicate conclusions from data analysis and visualization using the language of the discipline or interdiscipline.

As DA-AC learning goals mention DA-F courses, we list the DA-F learning goals for reference.

Data Analytics-Foundation Learning Goals and Outcomes:
DA-F-Goal 1: Obtain and analyze data.
DA-F Goal 2: Draw and critique conclusions from data analysis.
DA-F Goal 3: Communicate information from data analysis.

For a course to receive DA-AC approval, each of the DA-AC learning goals above must be Taught, Practiced, and Assessed.

Teaching can include lectures, notes, reading assignments, guided inquiry or a video.
Practice for the students can include homework, worksheets, or projects.
Assessments for the students can include graded homework, quizzes, exams, presentations, or reports.
Note:

- For a 4-credit course, at least 33% of the teaching practice, and assessments of the course should be directly related to the DA-AC learning goal
- For a 2-credit course, at least 75% of the course material should be directly related to DA-AC learning goals.

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