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Introduction to Data Visualization & Visual Perception

• Jeffrey A. Shaffer, Vice President at Unifund and Adjunct Faculty at the University of Cincinnati is the creator.
• Contact: (513) 615-0001, [email protected], @HighVizAbility

Goals

• Students will define data visualization and express its value as a tool for understanding.
• Fundamental aspects of visual perception and their relation to data visualization will be described..
• The history of data visualization, including key figures and contemporary practitioners will be learned
• Students will understand preattentive attributes, the meaning of color and size, and the two thinking systems used to process information.

Data Visualization and Reporting

• Clear and engaging visuals are used to explore data.
• Findings are shared through visual storytelling.
• Design principles make visuals professional.
• Charts and graphs are built step-by-step.
• Data Visualization simplifies complex data, reveals patterns and trends, and engages audiences.

Communicating Insights Through Data Visualization

• Communicating insights from data is an essential skill.
• Visuals are the most compelling way to share data stories.
• Key components of data visualization involve design, art, science and math.
• Visuals are more effective than summary statistics.
• Plots and charts, along with dashboards are commonly used.
• Design principles are used to improve visualizations.

Visual Analytics

• 2014 was a critical year for making complex analyses easier, dominating Business Intelligence (BI) market requirements.
• Data visualization classes are now being taught at universities as part of Business Analytics and other related fields
• Companies are adding visual analyst positions
• There are growing ranks of data storytellers and data visualization positions

Relevant Data Visualization Jobs (July 2017)

• Facebook needed a Data Visualization Designer/Storyteller.
• A Leading Hedge Fund sought a Data Visualization Expert.
• Deloitte was hiring for a Data Visualization Manager.

Business Intelligence: Moving from Data to Action

• Data leads to information which results in knowledge and finally a plan of strategy or key decision
• Data are facts and statistics collected for reference or analysis.
• Information are facts provided or learned.
• Knowledge is information and skills acquired through experience or education, understanding a subject theoretically or practically.
• Strategy involves a plan or action designed to achieve a goal.

What Business Intelligence Answers

• Data answers "How many?" and "How much?"
• Information contextualizes data.
• Knowledge seeks reasons with "Why?"
• Strategy tackles "How do we?" or "What can we do?"
• Visualization helps with quantity and some "why" questions

Analytics: A Brief History

• Claudius Ptolemy published "The Almagest" around 150 CE in Egypt; a treatise on astronomy.
• René Descartes (1596-1650) invented presenting number-based data using 2-D coordinate scales.
• William Playfair (1759-1823) was a Scottish engineer and economist who founded graphical methods of statistics, and created the time series line graph, bar chart and pie chart.
• Charles Minard (1781-1870) was a French civil engineer who produced graphics with multiple data points.
• Jacques Bertin (1918-2010) was a French cartographer and theorist who studied semiology and visual information.
• John Tukey (1915-2000) was an American statistician who published "Exploratory Data Analysis" and introduced the box plot in 1977.
• Edward R. Tufte (b. 1942) is an American statistician and Professor Emeritus at Yale University.
• William S. Cleveland is credited as a Contemporary Practitioner
  • Professor of Statistics and Courtesy Professor of Computer Science at Purdue University
  • Authored over 100 papers/publications including Visualizing Data (1993) and The Elements of Graphing Data (1994)
  • Initial developer of trellis charts, which make visualization possible in data sets with multiple variables
• Stephen Few is a contemporary practitioner
  • Prolific writer and author with a focus on designing simple information displays that are effective and communicative.
  • Author of "Show Me The Numbers (2004)", "Now You See It (2009)", "Information Dashboard Design"

Other Critical Events

• In 1984, the Apple Macintosh was introduced
• The Macintosh was the first affordable computer with interactive graphics.
• The graphical user interface and mouse were invented at Xerox PARC.

Building Blocks of Data Visualization

• Approximately 70% of sense receptors are in our eyes.
• 40% of the cerebral cortex processes visual information.
• Visual perception is intimately connected to understanding, as reflected in language.
• Long-term memory is important.
• Working memory limited to a small number of chunks.
• The sensory and emotional environments are important considerations

Key Guidelines for perception of data

• Shape
• Texture
• Orientation
• Value
• Color
• Size
• Position and Order

Built in biases

• System 1 (bottom up) operates automatically and quickly, with little effort or voluntary control and generates impressions, intuitions, intentions, and feelings for system 2.
• System 2 (top down) allocates attention to effortful mental activities, be engaged as needed to solve more complex problems or where System 1 runs into difficulty.
• Presentation impacts data perception.
• Mood and emotions impact critical thinking.
• Over-simplification can distort understanding.