Course Outline
Day 1:
- Understanding data visualization
- Why it matters
- Data visualization versus data mining
- Human cognition
- HMI
- Common pitfalls
Day 2:
- Types of curves
- Drill-down curves
- Plotting categorical data
- Multi-variable plots
- Data glyph and icon representation
Day 3:
- Plotting KPIs alongside data
- Examples of R and X charts
- ‘What-if’ dashboards
- Parallel axes mixing
- Combining categorical and numeric data
Day 4:
- Different roles in data visualization
- How data visualization can be misleading
- Disguised and hidden trends
- Case study: Student data
- Visual queries and region selection
Requirements
Participants should have some experience with plotting X-Y graphs, histograms, and scatter plots, along with a general understanding of data trends and time series graphing.
Testimonials (7)
I enjoyed the good real world examples, reviews of existing reports.
Ronald Parrish
Course - Data Visualization
I liked the examples.
Peter Coleman
Course - Data Visualization
I liked the examples.
Peter Coleman
Course - Data Visualization
I am a hands-on learner and this was something that he did a lot of.
Lisa Comfort
Course - Data Visualization
I really liked the content / Instructor.
Craig Roberson
Course - Data Visualization
Trainer was enthusiastic.
Diane Lucas
Course - Data Visualization
Learning about all the chart types and what they are used for. Learning the value of cluttering. Learning about the methods to show time data.