Course Outline
Day 1:
- Introduction to data visualization
- The significance of data visualization
- Distinctions between data visualization and data mining
- Principles of human cognition
- Human-Machine Interaction (HMI)
- Common pitfalls to avoid
Day 2:
- Various types of curves
- Drill-down curves
- Plotting categorical data
- Multi-variable plots
- Representation using data glyphs and icons
Day 3:
- Integrating KPIs with data
- Examples of R and X charts
- Interactive "what-if" dashboards
- Parallel axes mixing
- Combining categorical and numeric data
Day 4:
- The multifaceted roles of data visualization
- How data visualization can be misleading
- Recognizing disguised and hidden trends
- Case study: Student data analysis
- Visual queries and region selection
Requirements
A foundational understanding of X-Y graphs, histograms, and scatter plots is required, along with a general grasp of data trends and time series visualization.
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.