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Data Visualization

Visualization and presentation of data

Published by O'Reilly Media, Inc.

Intermediate content levelIntermediate

Using your data to make persuasive business cases

One of the challenges that professionals face is condensing spreadsheets, tables, and raw data into digestible information that can be displayed accurately in reports, PowerPoint slides, or even customer-facing marketing materials. You know your visualizations must be accurate, informative, and compelling, but choosing the best way to display your data can be a tricky task.

Expert Curtis Newbold walks you through the most effective methods for visualizing your data into charts, graphs, and maps. Along the way, you'll learn five specific questions to ask every time you're displaying data that will assist you in creating the most effective data visualizations for your purposes.

What you’ll learn and how you can apply it

By the end of this live online course, you’ll understand:

  • How the concepts of storytelling can be directly applied to the creation of data visualizations
  • How the nuances in design can affect the way people’s attention is drawn to particular pieces of data or information
  • How different types of charts and graphs can be utilized to display different types of data and information

And you’ll be able to:

  • Select the appropriate chart or graph for different types of data from among 25 common data visualization types
  • Identify appropriate storytelling techniques as they apply to data visualization
  • Approach data visualization with a designer’s mindset

This live event is for you because...

  • You're a business professional frequently tasked with developing charts or graphs to communicate your ideas, products, or research findings.
  • You're looking for new and more interesting ways to display data to those with whom you work or market to.
  • You're a team leader or manager who often has to use data and research to persuade employees to embrace new goals, processes, or policies.
  • You're an executive or top-level decision maker, and you frequently showcase data to pitch new products, services, and ideas to clients, investors, or other decision makers.

Prerequisites

  • This course is designed for any general businessperson and it does not require any specialized knowledge other than a very basic understanding that data can be moved from tables and raw formats into more visual means. Most participants will be familiar with the concepts of bar and pie charts, and probably line graphs and maybe even scatterplots. But the course, really, is designed to help broaden participants’ understanding of the types of data they work with regularly and the many, many options they have to represent their data.

Recommended follow-up:

Schedule

The time frames are only estimates and may vary according to how the class is progressing.

Roadmap (5 minutes)

  • Lecture: Explanation of course and purpose; roadmap for the course
  • Group discussion: What types of data do you work with in your profession? In which communication channels do you most often present this data—presentations, reports, marketing materials, press releases, white papers, or something else?

The value of visualizing data (10 minutes)

  • Lecture: How visuals make data meaningful; why data visualization is persuasive; a historical narrative—the United States Food Guide, 1940s–the present; information, misinformation, and disinformation; case studies—NBC Nightly News (“Race in America”), USA Today (“Colorado Marijuana Smuggling”), and Fox News (“Total Unemployed”)
  • Group discussion: In her book Storytelling with Data, Cole Nusbaumer describes an informal Twitter survey she conducted where she asked her followers to complete this sentence: “When someone asks me to ‘show’ them the data, I feel _________.” How would you respond to a similar question? How do you feel when you need to display data in a report, PowerPoint deck, or other medium?

Choosing the right chart (10 minutes)

  • Lecture: Determine what matters most—showing only what needs to be shown, narrowing and including data, and being cautious of manipulation; the five questions to ask yourself:
  • Does my data highlight just one important fact?
  • Am I trying to compare two or or more things?
  • Am I showing the results of a questionnaire?
  • Am I showing how parts of something relate to a whole?
  • Do I need to show how one dataset changes when affected by another dataset?
  • Group discussion: Which do you think you do the most?

The first two questions (30 minutes)

  • Lecture: Does my data highlight just one important fact?—large single number, icon array, donut or pie chart, faded bar graph; Does my dataset compare two or more things: general comparisons—bar chart, back-to-back graph, dot plot, line graph; comparing how things change over time—area graph, stacked column; comparing against a benchmark—benchmark line, bullet graph, indicator dots
  • Hands-on exercise: Using an example dataset and scenario, select the proper category and chart to use
  • Demonstration: Possible options; compare and contrast the value for each chart
  • Break (10 minutes)

The last three questions (35 minutes)

  • Lecture: Am I showing the results of a questionnaire?—stacked bar, small multiples, column graph, numbers with icons, nested area graph; Am I showing how parts of something relate to a whole?—pie chart, 100% stacked bar, histogram, treemap, geomap; Am I showing how one dataset changes when affected by another dataset?—scatterplot, diagram, detailed description
  • Hands-on exercise: Using an example dataset and scenario, select the proper category and chart to use
  • Demonstration: Possible options; compare and contrast the value for each chart

Other options and qualitative data (5 minutes)

  • Lecture: Words, not numbers; word clouds; pictures; heat maps; Is visualization the best method?
  • Group discussion: When do you feel data visualizations are 1) absolutely necessary; 2) a good option, but not critical; or 3) typically a bad idea?

Data visualization in the workplace (10 minutes)

  • Lecture: Using data visualizations to clarify; using data visualizations to persuade; using data visualizations to market products or ideas; inserting data visualizations into documents—often include a narrative, even if implied, should stand alone, but may be stronger with supplemental info, more persuasive with introduction and summary

Wrap-up and Q&A (5 minutes)

Your Instructor

  • Curtis Newbold

    Curtis Newbold is a passionate educator, speaker, and award-winning corporate consultant with a love for all things communication. He has designed and delivered courses, workshops, webinars, and presentations on scores of topics such as information design, data visualization, leadership communication, brand strategy, presentation delivery, business writing, and public relations management. Curtis has led graduate student marketing and communication projects in Peru, South Africa, Cambodia, Hungary, Morocco, and Iceland and he has taught at multiple universities in the United States and China. Curtis is the owner and chief content architect for the popular communications blog, TheVisualCommunicationGuy.com and is co-author of a textbook-in-progress, Business and Professional Communication, with Sage Publications. He currently serves as Clinical Associate Professor of Strategic Communication at the University of Utah and he holds a PhD in Rhetorics, Communication, and Information Design from Clemson University.

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