teaching with tableau: showing insights and telling data-driven

Teaching with Tableau: Showing insights

and telling data-driven stories

Professor Kristen Sosulski

Today’s Speaker

Kristen Sosulski, Ed.D

Associate Professor

Director of Education

W. R. Berkley Innovation Lab

New York University

Leonard N. Stern School of Business

Bio

Dr. Kristen Sosulski develops innovative practices for higher education as the Director of

Education for the NYU Stern W.R. Berkley Innovation Lab. She also teaches MBA

students and executives data visualization, R programming, and operations management as

an Associate Professor at NYU’s Stern School of Business.

As a leading expert on data visualization, Kristen regularly consults, delivers seminars, and

leads workshops on data visualization techniques and best practices. You can find her

speaking on the subject at events like Social Media Week NYC and to organizations like

the National Association of Pubic Opinion, Digital Analytics Association, and the National

Economic Research Associates.

Follow Kristen on Twitter at @sosulski and learn more at http://kristensosulski.com

http://twitter.com/sosulski

http://kristensosulski.com

College/University Background

Course 1: Data Visualization

Audience: 50 MBA students from NYU Stern

Format: Blended Online

Course 2: Data Visualization

Audience: 70 NYU Stern Master Science in Business Analytics students

Format: Intensive 2-day session with asynchronous online activities

The Challenge

In data visualization courses, students learn to present data in visual form. This involves

working with data, learning new software, and applying visual design principles.

Sometimes imaging software by default enables us to create beautiful visualizations.

However, designing visualizations that are readable and provide key insights is much more

difficult.

Visualizations are only as effective as the insights they reveal.

How can professors support students in their process of creating purposeful and

interpretable visualizations and use they as powerful tools in their presentations?

As visualization designers we are “melding the skills of computer science, statistics, artistic design, and storytelling.”

K. Cukier (2010). Show me: New ways of visualizing data.

http://www.economist.com/node/15557455

Visualization is a translation process

Real world DataShapes and

colors

My courses in data visualization are designed to provide students with the

techniques to communicate insights, allow them to apply those techniques, and to

receive feedback on how well they’ve applied those techniques.

This done through 1) demonstration 2) practice & application 3) critique

and 4) expert and peer feedback.

PART I: The use of software to support data presentation

in visual form

PART II: Using visualizations effectively in a presentation

PART III: Application, practice, & feedback

Three features to build into your visualizations

1. Annotation: To highlight and direct the user’s attention.

2. Animation: To walk the user through the visualization, step by step. To show

and explain the data points at a slower pace.

3. Interactivity: To provide summary level data and details on demand. To

engage and involve the audience.

Annotation and encodings

• Emphasize the purposeful use of pre-attentive attributes.

• Highlight a data point, using a pre-attentive attribute.

• Avoid highlighting every data point.

• Reserve the use of pre-attentive attributes as cues for your audience.

This can be easily done in Tableau.

Animation

• To progressively reveal content.

• To mark specific data points at specific times.

• To show time series data.

Animations work well for showing times series data for one or more categories.

Animations allow the user to start, stop, rewind, and fast forward.

Animation provides a navigational feature to a visualization.

Trend animation

• Trend animation shows all trends simultaneously.

• It works best for presentation rather than analysis.

• It is limited to approximately 200 data points on a single display.

• Use the pages card

• Drag year (or time-based

data) to the pages card

• Filter time series data

using the filters card

• Determine the speed

(slow, normal, or fast)

• Select color of encodings

from the marks card.

Trace animation

• Trace animation uses fade-in bubbles/links to show the direction of the

flow of data points and history.

• Traces work best for analysis when the result is not cluttered.

• Beware of too many data points and visual clutter.

• Consider small multiples for analysis rather than animation.

• Select Show History from the Pages marks card.

• Select show history for all

• Select show Marks

• Select a color and transparency for the marks

Transition animation

• Short animation keeps users in context during view/data

transitions.

• These usually follow an action, such as connect, select, or

explore, for interactive displays.

• Click to highlight the

data point that you want

to keep highlighted

• Works nicely when

combined with trace

animation for time

series data where

categories change over

time.

Interactivity

• To enable audience interaction and involvement

• To filter details on demand

• To traverse the data set to compare and contrast different

attributes.

Slider

Input field

HighlightFilter


in visual form


PART III: Application, practice, and feedback

Three techniques for presentation

Technique #1: Identify the key takeaway

• Provide clear takeaways for each visualization.

• Write it in the notes or the title of the slide.

Today, the largest shipping ports are in Asia, with three of five located in China.

Kristen Sosulski | Source: World Bank - Container Port Traffic (2014).

36

Technique #2: Put your findings in context

• Provide a context for your findings.

• Without a context, data is meaningless.

• In the example on the next slide, an insight is communicated that puts the

number one position (Shanghai) in context and provides an explanation for

the rise to the top.

Since 2004 the capacity at the Port of Shanghai has grown from 14 million TEUs to more than 32 million in 2013, giving rise to its # 1 position in terms of TEU volume.

Kristen Sosulski | Source: World Bank - Container Port Traffic (2014).

Technique #3: Present the key numbers

• It is important to summarize the key findings and present the numbers in a

meaningful context that is comprehensible to the audience.

• For example, it may be more helpful to show a percentage change from year

to year when presenting an increase over time, rather than with absolute

numbers.

• Specifically, if the core point is to compare the change from year to year,

percentage change is an effective metric.

20,172.3

23,640.2 24,41625,816.8 26,433.5

2010 2011 2012 2013 2014

China’s total import and export value from 2010 to 2014 (in billion Yuan)

There was a 31% increase from 2010 to 2014

Kristen Sosulski | Source: Statistica (2014).

Summary

By incorporating these tips students can tell better stories with their data and use

visualizations to reveal important insights about the data

Identify the takeaway Contextualize findings Present the key numbers


in visual form


PART III: Application, practice, and feedback

Application: How do you have students practice applying these techniques?

Individual Project

1) 2 minute live presentation

2) 2 minute video presentation

Group Project

20 minute live presentation with peer feedback and critique

Individual Project

34 PITCHES

2 MINUTES EACH

NOTE &

Student / Peer voting criteria

DISCUSS

Instructor - Assessment Rubric: Individual Project

Criteria0 = Lacking, 3 = Excellent

Creative Idea 3

Compelling Idea 3

Well-conceived idea 2

Clear proof of concept 2

Visuals targeted @ appropriate audience 1

Data represented accurately 2

Data represented adequately 2

Visuals exhibit good design principles 3

Well-designed slide presentation 3

Persuasive / compelling presentation 2

Observed Pitfalls

• Over time limit (#4)

• Talked over visuals without explicitly referencing them (#8)

• Looking at the board

• Lack of audience engagement (#1)

• Lack of a clear vision or story (#1, #7)

• Too much information (#5)

Group project

Proposed workflow

Plan Storyboard Design BuildRehearse, test, and

revise

• 20 minutes

• 10 minute Q & A

• All team members must be present, but all do not have to present. Peer feedback and ratings will be factored into your grade.

• Review the presentation testing & delivery standards

• Is sitting the new smoking?

• Refugee crisis: Is it really that bad?

• Measuring good neighbors: Social cohesion index

• Do you believe in UFO sightings?

• Use movie compass to pick your next flick.

• Making decisions about student loan debt and college

• Election outcome prediction. Can twitter data help?

• How does AirBnB affect branded hotels?

• Twitter and the response to current events

Group project topics

Audience guidelines and role

• No laptops

• Respond to prompts by the presenters (if applicable)

• Take note of what worked well and areas for refinement

• Share you comments and feedback with the team during the critique

Critique – 10 minutes

• How well did the team tell a story with data?

• How well did the team select visual displays to present their data?

• How well did the team do at communicating key insights?

• What are the key takeaways from the presentation?

• What worked well? Do you have suggestions for future work?

Assessment Rubric: Group Projects

What worked well?

• Concise stories

• Use of data and visuals as evidence

• Questions or prompts for the audience

• Dynamic presenters

• Interesting data and presentation of that data

• Data points were put in context

• Provided reference points or points of comparison

Interesting in learning more and keeping in touch?

Go to my website and sign up for my mailing list at:

http://bit.ly/datavisupdates

You’ll immediately receive access to:

“Ten common pitfalls for presentations and data

visualizations?

http://bit.ly/datavisupdates

Upcoming Talks

May 16th: Digital Analytics Association - Engaged

Storytelling with Information Visualization: Techniques for

Audience and Presenter Driven Stories

November 16th: Plot Com. The Plot.ly Conference

Live Q&A

teaching with tableau: showing insights and telling data-driven

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