Course Outline
Day 1:
- Introduction to data visualization
- The significance of data visualization
- Contrasting data visualization with data mining
- Principles of human cognition
- Human-Machine Interface (HMI)
- Common pitfalls to avoid
Day 2:
- Exploring various curve types
- Drill-down curves
- Plotting categorical data
- Multi-variable plots
- Data glyph and icon representation
Day 3:
- Integrating KPIs with data
- R and X charts examples
- Interactive 'what if' dashboards
- Parallel axes mixing
- Combining categorical and numeric data
Day 4:
- Different roles in data visualization
- How data visualization can be misleading
- Identifying disguised and hidden trends
- Case study: Analysis of student data
- Visual queries and region selection
Requirements
A foundational understanding of data plotting techniques, including X-Y graphs, histograms, and scatter plots, along with a general grasp of data trends and time series analysis.
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.
