Course Outline

Day 1:

  • what is data visualization
  • why it is important
  • data visualization vs data mining
  • human cognition
  • HMI
  • common pitfalls

Day 2:

  • different type of curves
  • drill down curves
  • categorical data plotting
  • multi variable plots
  • data glyph and icon representation

Day 3:

  • plotting KPIs with data
  • R and X charts examples
  • what if dashboards
  • parallel axes mixing
  • categorical data with numeric data

Day 4:

  • different hats of data visualization
  • how can data visualization lie
  • disguised and hidden trends
  • a case study of student data
  • visual queries and region selection

Requirements

Some knowledge on data plotting X-Y graphs, histograms and scatter plots plus a general understanding of trends in data and time series graphing.

  28 Hours
 

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