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Data Science

Introduction to Data Visualization

GROUP TRAINING

Overview

We are constantly faced with a vast amount of complex information – often more than we can handle. Well-designed visual interpretations of data improve comprehension, communication, and decision making.

This workshop introduces data methods and techniques that increase the understanding of complex data. The focus is on conveying ideas effectively with visually appealing charts, graphs and maps.

Participants will learn to craft clear, meaningful pictures of complex statistics and publicly available data through the creation of effective graphs and charts.

Why You Should Take This Course

Upon successful completion of this course, students will be able to:

  • Apply critical thinking to visualization work
  • Practice reading and interpreting charts
  • Identify story angles in data
  • Assess the use of chart types
  • Make appropriate design choices
  • Practice developing design concept solutions for given situations
  • Explain how data visualization helps in the analysis and understanding of complex data
  • Explain how people process and perceive images
  • Be able to critique visualizations and identify the design principles used to create them
  • Use good design practices for visualization
  • Clearly communicate data with annotated timelines and motion charts.

Course Outline

Introduction to Data Visualization

The Context of Data Visualization
  • The data visualization methodology
  • Visualization design objectives
  • The interaction of form and function
  • Justifying design selections
  • Creating accessibility
  • Ethics
  • The “eight hats” of data visualization design
Setting the Purpose and Identifying Key Factors
  • Clarifying the purpose of your project
  • Establishing intent – the visualization’s function (explain, explore, exhibit, entertain)
  • Establishing tone
  • The importance of editorial focus
  • Preparing and familiarizing yourself with your data
  • Using visual analysis to find stories
Visualization Design Options              

The visualization anatomy – data representation

  • Choosing the correct visualization method
  • Considering the physical properties of our data
  • Determining the degree of accuracy in interpretation
  • Creating an appropriate design metaphor
  • Choosing the final solution

The visualization anatomy – data presentation

  • The use of color
  • Creating interactivity
  • Annotation
  • Arrangement
Data visualization methods, choosing the appropriate chart type
  • Comparing categories (Dot plot, Bar chart )
  • Assessing hierarchies and part-to-whole relationships (pie chart, stacked bar chart)
  • Showing changes over time (sparklines, area charts)
  • Plotting connections and relationships (Scatter plot, heat map )
  • Mapping Geo-spatial data (Cloropleth, dot lot map)
Constructing and Evaluating Your Design Solution
  • Visualization Charting statistical analysis tools
  • The construction process
  • Evaluating the work of others
  • Developing your capabilities
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