MGMT 1316: Quantitative Business Analysis: Fall 2024: Data Visualization

Creating effective charts and data visualizations involves a blend of art and science.

Consider the following when creating your visualizations:

• Understand your audience and purpose. 
  • Know your audience. 
    • Consider the background knowledge level, and expectations of your audience. This will guide the complexity and type of visualization you choose.
  • Define the purpose
    • Clearly understand what you want to communicate. Are you explaining a trend, comparing data, showing relationships, or presenting distributions.
• Choose the right type of chart or visualization.
  • Bar Chart: Ideal for comparing quantities across different categories.
  • Line Chart: Best for showing trends over time.
  • Pie Chart: Useful for showing proportions within a whole.
  • Scatter Plot: Great for showing relationships or correlations between two variables. 
  • Histogram: Used for showing distributions of a single variable
  • Heatmap: Effective for displaying data density or patterns across two dimensions
• Simplify and clarify.
  • Remove unnecessary element. 
    • Eliminate things such as 3D effects, excessive gridlines, too many colors, or other distracting details.
  • Use labels wisely.
    • Make sure labels are clear and concise. Label axes, data points, and legends
• Make it accessible.
  • Consider using color palettes that are color blind friendly. (i.e. blue and red)
  • Use high contrast to ensure text and data points stand out against the background.
  • If your chart will be viewed online provide descriptions for screen readers. 
• Use color and size effectively
  • Color
    • Use color to highlight important data, differentiate categories, or indicate changes over time. 
    • Avoid using too many colors
  • Size
    • Use size to show magnitude in bubble charts or highlight significant data points.
• Ensure Data Accuracy and Integrity 
  • Check for accuracy
    • Ensure your data is correct and the visualization represents the underlying data.
    • Avoid misleading visuals.
• Tell a Story
  • Highlight key insights by using annotations, titles, and callouts to important aspects of the data. 
  • Create a narrative flow by arranging charts in a logical order

Common Issues to Avoid

• Overloading with Information
  • Too much data on one chart can be overwhelming
• Improper Scaling
  • Inconsistent scales on axes can misrepresent the data and mislead the audience.
• Inconsistent Style
  • Keep charts consistent in style, color, and format.