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Data Visualization for Data Analysts and Analytics

Data Visualization for Data Analysts and Analytics

1h 44mIntermediate2024-06-14

Authors

Bill Shander

Bill Shander

CEO and Founder of Beehive Media

Course details

As a data analyst, you probably already know how to build visualizations and use tools like Excel and Tableau. This course challenges you to go beyond the data, beyond the software, and start thinking more clearly and strategically about the foundations of great communication design. Bill Shander, founder of Beehive Media, focuses on the key challenges that analysts face trying to communicate complex information, and how visual communication can help. Bill takes a deep dive into important strategies for visual analysis. He then breaks down ten key components of great data visualizations—built in any program—and shows innovative ways of rethinking the slides, charts, diagrams, and dashboards you work with every day.

Learning objectives
Describe the importance of audience and story in designing visual presentations.
Identify Gestalt principles for visual processing.
Compare and contrast headline styles.
List general rules for the use of different chart types, colors, axes, and other formatting details.
Understand the importance of and scientific basis for guiding principles in presentation design.

Skills covered

Data VisualizationData ScienceBusiness Analysis and StrategyBusiness Software and ToolsOne-Off

Concepts

0. Introduction

  • 01 - Moving from analysis to visualization

1. Why

  • 02 - Humans are visual creatures
  • 03 - Understanding visual perception
  • 04 - Meeting communications challenges
  • 05 - Focus using the KWYs

2. Visual Analysis in Six Easy Lessons

  • 06 - Where to begin Matrix heatmaps
  • 07 - Where to go next Distributions
  • 08 - Scatterplot mania
  • 09 - Bars, pies, and lines, why not
  • 10 - Benchmarking everything
  • 11 - Quick and ugly is fine

3. Visual Communication in 10 Easy Lessons

  • 12 - Using the right data
  • 13 - The power of story
  • 14 - Headlines bring focus
  • 15 - Picking the right chart
  • 16 - Simple tips and tools for using color in data visualization
  • 17 - Tips for axes, labeling, and legends
  • 18 - Setting scales in data visualization
  • 19 - Some thoughts about tools
  • 20 - Sketching and wireframing
  • 21 - What about leave-behinds

4. In Practice

  • 22 - Finding the missing link with visuals
  • 23 - Rethinking some charts
  • 24 - The power of simplification - Convincing your bosses

5. Conclusion

  • 25 - Further resources

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