Data Visualization - What can you see? #baai17
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My presentation slides form my talk at the Annual Conference of the Business Analysts Association of Ireland - 19th May, 2017.
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Data Visualization - What can you see? #baai17
- 1. Dr Eugene F.M. O’Loughlin National College of Ireland Data Visualization What Can You See?
- 2. Agenda History Lesson The Democratization of Data Making Sense of Data New Challenges to Big Data Visualization Data Presentation Data Visualization tools Short Exercise
- 3. Data Visualization - 1786 Source: Commercial and Political Atlas (Playfair, 1786)
- 4. Charles Joseph Minard (1869) Image source: Wikimedia Commons.
- 5. Broad Street Pump (source of contaminated water) London Cholera Epidemic Clusters (Snow, 1854)Imagesource:WikimediaCommons.
- 6. Today – YouTube Analytics www.youtube.com/eoloughlin
- 7. Drill down…
- 8. Definition of Data Visualization (Kirk, 2016)
- 9. Why is data visualization important? (sas.com) Because of the way the human brain processes information, using charts or graphs to visualize large amounts of complex data is easier than poring over spreadsheets or reports Image source: https://projectyourself.com/wp-content/uploads/sites/4/2014/08/Depositphotos_10171240_l.jpg
- 10. Top Down Processing Theory Psychologist Richard Gregory (1970) argued that perception is a constructive process which relies on top- down processing Stimulus information from our environment is frequently ambiguousGregory, R. (1970). The Intelligent Eye. London: Weidenfeld and Nicolson.
- 11. Perceptions can be ambiguous The Necker Cube
- 12. Non-realizable Objects Four ≠ Three
- 13. What do you see?
- 14. The Democratization of Data Employees who aren’t data scientists or analysts should be able to: ◦ ask questions of the data based on their own business expertise ◦ quickly and easily find patterns ◦ spot inconsistencies ◦ get answers to questions they haven’t yet thought to ask
- 15. “Small” Data – Easy! New challenges to data visualization Image source: https://thombartley.wordpress.com/2014/05/08/big-social-vs-little-social/
- 16. Visualizing Big Data Big data brings new challenges to visualization: ◦ Speed of data ◦ Size of Data ◦ Diversity of data ◦ Cardinality Move beyond comfort zone because of: ◦ Volume ◦ Variety ◦ Velocity Image source: https://rc.fas.harvard.edu/how-big-is-big-data/
- 17. Big Data - Value One of the major challenges of big data is how to extract value from it We know how to ◦ create it ◦ store it But we fall short when it comes to ◦ analysis ◦ synthesis
- 18. Visualizing Big Data Handling large volumes
- 19. Visualizing Big Data Correlation Matrix
- 20. Visualizing Big Data Time Series/Forecasting
- 21. Visualizing Big Data Sankey Diagram
- 22. Visualizing Big Data Fun & Challenging! However… ◦ Wrong visualization? ◦ Audience? ◦ Consider more than one visual? Important ◦ How do viewers process visual information? ◦ Do you understand the composition and relationships in your data? Poor Data Visualization Ahead Image source: http://www.clipartbro.com/clipart-image/warnign-sign-clipart-26760
- 23. Data Presentation To derive understanding from data we need to see it represented in a different, visual form Anatomy of a chart: ◦ Marks Points Lines Areas ◦ Attributes Size Colour Position Image source: http://www.pngmart.com/image/tag/lionel-messi 0 10 20 30 40 50 60 Lional Messi: Games and Goals for FC Barcelona Appearances
- 24. Facilitating Understanding The Three Stages of Understanding Perceiving Interpreting Comprehending What does it show? Where is big, medium, small? How do things compare? What relationships exist? What does it mean? What is good and bad? Is it meaningful or insignificant? Unusual or expected What does it mean to me? Where are the main messages? What have I learnt? Any actions to take? Kirk (2016)
- 25. Importance of Context 0 10 20 30 40 50 60 Lional Messi: Games and Goals for FC Barcelona Appearances 0 10 20 30 40 50 60 Total Sightings of Winglets and Spungles Winglets
- 26. Will it Make the Boat go Faster? • Focus on performance Great Britain Men’s Eight Rowing Team (Sydney Olympics, 2012) Images sourced: http://www.willitmaketheboatgofaster.com
- 27. Good Design (Andy Kirk, 2016) The Three Principles of Good Visualization Design Principle 1 Good data visualization is TRUSTWORTHY Principle 2 Good data visualization is ACCESSIBLE Principle 3 Good data visualization is ELEGANT
- 28. Fragility of Trust (Figure-ground Perception) Image source: Business Insider. Image source: Business Insider. Principle 1 Good data visualization is TRUSTWORTHY
- 29. Reward vs Effort Effort ◦ Act of understanding Reward ◦ Achieving of understanding You can’t force viewers to understand (but you can smooth the way) Know your audience Principle 2 Good data visualization is ACCESSIBLE
- 30. Elegant Design How do you achieve elegance in design? ◦ Eliminate the arbitrary ◦ Thoroughness ◦ Style ◦ Decoration should be additive, not negative Principle 3 Good data visualization is ELEGANT Image source: Wall Street Journal.
- 31. If you're explaining, you're losing. The Reagan Diaries (2007) Image source: https://en.wikipedia.org/wiki/Ronald_Reagan Image source: https://en.wikipedia.org/wiki/United_States_presidential_election,_1984
- 33. Exercise: Data Visualization Find all possible ways to visualize a (ludicrously) small data set of just two numbers 75 37
- 34. Questions
Editor's Notes
- William Playfair's trade-balance time-series chart, published in his Commercial and Political Atlas (1786)
- Wikipedia Page: https://en.wikipedia.org/wiki/Charles_Joseph_Minard Figurative Map of the successive losses in men of the French Army in the Russian campaign 1812-1813. Drawn by Mr. Minard, Inspector General of Bridges and Roads in retirement. Paris, 20 November 1869. The numbers of men present are represented by the widths of the colored zones in a rate of one millimeter for ten thousand men; these are also written beside the zones. Red designates men moving into Russia, black those on retreat. — The informations used for drawing the map were taken from the works of Messrs. Chiers, de Ségur, de Fezensac, de Chambray and the unpublished diary of Jacob, pharmacist of the Army since 28 October. In order to facilitate the judgement of the eye regarding the diminution of the army, I supposed that the troops under Prince Jèrôme and under Marshal Davoust, who were sent to Minsk and Mobilow and who rejoined near Orscha and Witebsk, had always marched with the army. Niemen River shown is in modern day Lithuania (Kowno on map = city of Kaunas). Charles Minard's map of Napoleon's disastrous Russian campaign of 1812. The graphic is notable for its representation in two dimensions of six types of data: Number of Napoleon's troops Distance Temperature Latitude and longitude Direction of travel Location relative to specific dates
- The word “representation” is deliberately positioned near the front of the definition because it is the quintessential activity of data visualization deign.
- Data visualization is a quick, easy way to convey concepts in a universal manner – and you can experiment with different scenarios by making slight adjustments
- Gregory, R. (1970). The Intelligent Eye. London: Weidenfeld and Nicolson (NOT IN NCI LIBRARY). Material on this and next slide taken from: http://www.simplypsychology.org/perception-theories.html To interpret it, we require higher cognitive information either from past experiences or stored knowledge in order to makes inferences about what we perceive. For Gregory perception is a hypothesis, which is based on prior knowledge. In this way we are actively constructing our perception of reality based on our environment and stored information.
- The Necker cube is a good example of this. When you stare at the crosses on the cube the orientation can suddenly change, or 'flip'. It becomes unstable and a single physical pattern can produce two perceptions. Gregory argued that this object appears to flip between orientations because the brain develops two equally plausible hypotheses and is unable to decide between them. When the perception changes though there is no change of the sensory input, the change of appearance cannot be due to bottom-up processing. It must be set downwards by the prevailing perceptual hypothesis of what is near and what is far.
- In this image you see four boards if you look to the left of the image but when you look to the right you see three. When you look directly in the middle its almost impossible to tell how many boards there are. This is possible because by drawing some lines in on the left side and not keeping them consistent with the right side your brain doesn’t process how many actual boards there are.
- You see a couple in an intimate pose. Right? Interestingly, young children immediately see nine dolphins. They do not see the intimate couple because they have no prior memory associated with such a scenario. Look again at the bottle. Do you see the nine dolphins now? If not, here’s help. Look at the space between the woman’s right arm and her head. The tail is on her neck; follow it up. Look at her left hip. Follow the shaded part down; it’s another one. And on his shoulder … do you see them now? Of the nine dolphins in the picture, seven are at least as long as the woman’s upper arm, one is the size of the man’s left hand, and another is the size of the woman’s forehead. By focusing your attention in a different way (focusing on the dark shapes instead of the light ones your memory recognizes), you changed your perception of the pattern thereby allowing yourself to see something that you could not otherwise see. Similarly, the creative thinking techniques in Michael’s books will change the way you think by enabling you to look at the same information as everyone else and see something different. - See more at: http://creativethinking.net/nine-dolphins/#sthash.Fej9g4JN.dpuf
- Volume refers to the size of the data. Variety describes whether the data is structured, semi-structured or unstructured. Velocity is the speed at which data pours in and how frequently it changes. Cardinality: uniqueness of data values contained in a column. High: large percentage of unique values (eg bank a/c numbers). Low: lot of repeat values (eg, gender)
- Analysis – break down Synthesis – put together again
- SAS Visual Analytics provides autocharting and “what does it mean” pop-ups to help nontechnical users create and understand data visualizations. The “what does it mean” pop-up (bottom) explains that the correlation shown in this binned box plot indicates a strong linear relationship between Sales Rep Rating and Vendor Satisfaction.
- A correlation matrix combines big data and fast response times to quickly identify which variables among the millions or billions are related. It also shows how strong the relationship is between the variables. In this correlation matrix, darker boxes indicate a stronger correlation; lighter boxes indicate a weaker correlation. You can double-click on a box for further details.
- With automated forecasting capabilities, SAS Visual Analytics chooses the most appropriate forecasting algorithm for the selected data. “What does it mean” pop-ups (bottom of screen) provides explanations of analytic functions and data correlations, so even nontechnical users can understand what the data means.
- Sankey diagrams use path analysis to show the dynamics of how transactions move through a system (e.g., how customers navigate your website). A Sankey diagram displays a series of linked nodes, where the width of each node indicates the frequency of the link or value of the measure.
- Visualizing your data can be both fun and challenging. It is much easier to understand information in a visual compared to a large table with lots of rows and columns. However, with the many visually exciting choices available, it is possible that the visual creator may end up presenting the information using the wrong visualization. In some cases, there are specific visuals you should use for certain data. In other instances, your audience may dictate which visualization you present. In the latter scenario, showing your audience an alternative visual that conveys the data more clearly may provide just the information that’s needed to truly understand the data.
- What does chart tell you?
- Same data on both charts! On left – Lionel Messi data from slide 3. On right – Winglets and Spungles (completely made up words)
- Will It Make The Boat Go Faster? was born out the story of an ordinary guy achieving something extraordinary. In 1998, consistently failing to medal or even make the final of major regattas, the GB Men’s Rowing Eight decided to fundamentally change the way they worked and how they worked with each other. Their focus became purely about performance, the results they hoped would follow. They approached things differently, critically asking the same question with every single action they took… Will It Make The Boat Go Faster? Along their journey they learnt the sustainable, dependable techniques and behaviours that drove continuous team improvement. The outcome 18 months later, against all reasonable odds, was a stunning Olympic Gold on the waters of Sydney.
- Is my visualization design good visual design?
- From: http://www.businessinsider.com/gun-deaths-in-florida-increased-with-stand-your-ground-2014-2?IR=T Gun deaths in Florida started out high in the 1990s (when crime was higher everywhere in America) and gradually declined throughout the decade and into the 2000s. Then, in 2005, when the stand your ground law was enacted, murders involving firearms spiked by more than 200 in two years. The stand your ground provision in Florida's self-defense law states: A person who is not engaged in an unlawful activity and who is attacked in any other place where he or she has a right to be has no duty to retreat and has the right to stand his or her ground and meet force with force, including deadly force if he or she reasonably believes it is necessary to do so to prevent death or great bodily harm to himself or herself or another or to prevent the commission of a forcible felony. In other states without stand your ground provisions, people must usually attempt to flee before using deadly force. These states are known as "duty to retreat" states. There's some disagreement about whether stand your ground laws lead to increased gun deaths. Some researchers point out that states with stand your ground laws tend to see an increase in homicides after the law is enacted, NPR reports. But McClatchy D.C. reports that the evidence is mixed, noting that not every state that has passed a "stand your ground" law has seen an uptick in homicides. Note: BI reader P.A. Fedewa created an easier-to-read version of the above chart from Reuters. It more clearly shows that gun deaths increased between 2005 and 2007 by flipping the y-axis. We're adding it to this post with his permission. The original chart and graphic design was done by Reuters.
- Graphic: Offers an elegant and appealing presentation that is in harmony with its subject.
- http://www.scribblelive.com/blog/2012/07/27/45-ways-to-communicate-two-quantities/ Information visualization is a language.
- Image from: http://jenchristiansen.com/?p=17 Batodonoides vanhouteni A reconstruction of the smallest known non-flying mammal (left), with a modern Etruscan shrew (right) for scale; illustration © National Geographic