DSBA 5122: Visual Analytics & Storytelling
University of North Carolina, Charlotte
The data science cycle includes many phases, including problem definition, data acquisition, data engineering, analysis, reporting, interpreting, visualization, and presentation of the results of analysis/insights derived. This course covers the last three steps in this sequence. It introduces the field of visual analytics, which integrates interactive analytical methods and visualization, and utilizes this to build analytical stories that�influence decision makers.� Topics include: critical thinking, visual reasoning, perception/cognition, principles of interaction with an audience, building of visuals into a story to�influence, and delivery of presentations whether�in person or through video conferencing tools.
Average GPA: 3.88
Grade distribution records: 1,125 students across 28 terms.
Grade distribution
| Grade | Students | Percent |
|---|---|---|
| A | 973 | 86.5% |
| B | 127 | 11.3% |
| C | 5 | 0.4% |
| W | 13 | 1.2% |
Based on 1,125 student grade records across 28 terms and 13 professors.
Instructors
- Wenwen Dou 461 students, Average GPA 3.90
- Chase Romano 223 students, Average GPA 3.90
- Robert Fox 89 students, Average GPA 3.78
- Jinwen Qiu 80 students, Average GPA 3.80
- Ryan Wesslen 71 students, Average GPA 3.83
- Ilieva Ageenko 59 students, Average GPA 3.90
- Stephen Rohrer 28 students, Average GPA 3.93
- Steven Jordan 28 students, Average GPA 3.71
- Isaac Cho 27 students, Average GPA 3.93
- Marcus Ellis 22 students, Average GPA 4.00
- Atif Farid Mohammad 20 students, Average GPA 3.90
- Jing Yang 13 students, Average GPA 3.77
- Aidong Lu 4 students, Average GPA 4.00