Visualization Best Practices Webinar
Download as PPTX, PDF0 likes60 views
The document discusses data visualization best practices, emphasizing the importance of understanding different user needs and perspectives when creating visuals. It highlights the significance of applying visual and cognitive neuroscience principles to design intuitive visuals and describes various types of analytical visuals tailored for strategic, operational, and analytical purposes. Additionally, it outlines a methodology for effective visual design, incorporating audience engagement and iterative feedback to enhance clarity and utility.
Visualization Best Practices Webinar
- 1. Karen Ragotte Marketing Director December 5, 2019 Data Visualization Best Practices Eric Tobias VP, Analytics Services
- 3. service provider reseller Focus on Tableau Since 2013 dashboards training data preparation server
- 4. 350+ Tableau engagements 1200+ Tableau dashboards built 2800+ Tableau users trained Tableau Expertise
- 6. Data Visualization Best Practices Webinar
- 7. According to Stephen Few, one of the original data visualization evangelists: A visual is a visual display of the most important information needed to achieve one or more objectives; consolidated and arranged on a single screen so the information can be monitored at a glance.
- 8. Not all users are the same: ◦ Not all users have the same level of analytical expertise. ◦ Not all users have the same familiarity with the subject matter. ◦ Not all users answer questions from the same perspective. It is highly unlikely, or desired, to meet these disparate needs with a single visual.
- 9. There are three general types of analytical visuals that address end user needs: ◦ Strategic/Executive – A high level view of a question or line of inquiry ◦ Operational – A regularly updated answer to a question or line of inquiry ◦ Analytical – Interactive view providing mechanisms for a variety of investigations on a specific topic. Knowing the type of visual you’re creating prior to even starting will help you focus the design efforts as you get started.
- 10. Data Visualization Best Practices Webinar
- 11. The study of the neural processes in the brain underlying visual perceptive and cognitive functions.
- 12. What is the difference between perception and cognition? ◦ Perception is the organization, identification, and interpretation of stimuli from your senses. An overly simplified way to describe is acquiring information through the senses. ◦ Cognition is the processing of information and acquiring knowledge through reason, intuition, and perception. A simpler way to think of it is cognition is the processing of perception into knowledge. Perception is fast, cognition is much slower. Is there something we can do with this information?
- 13. How is this relevant to us? ◦ We can make use of visual perception principles and design visuals that result in an immediate understanding of the information that is arising from the data. Visuals that properly implement the findings of visual and cognitive neuroscience will result in “intuitive” visuals. The recommendations derived from visual and cognitive neuroscience are referred to as “visual best practices” or VBP Let’s look at a couple of examples… in each example one visual properly implements VBP, while the other does not. Let’s see if you can guess which is which.
- 16. Data Visualization Best Practices Webinar
- 17. Seeing (perception) and comprehending (cognition) occur all the time, every day from second to second. The shorter the time between “seeing” and “comprehending”, the more productive your end users will be and the more “intuitive” your visualization will be. You should apply scientific findings when designing your visuals. Above all else, understand what works in what situations, what does not, and the difference between the two.
- 18. The human brain can process small amounts of visual information very quickly, but only for a very short period. This is called “Visual Short-Term Memory” (VSTM). Each element in the visual must be “seen” (perception) within roughly 40 milliseconds… any longer and it must be processed “attentively” (cognition). If you take advantage of VSTM your end-users can interpret entire visuals within a few seconds. To make use of VSTM requires us to know what works and what does not work when visual processing is occurring. Things that work well with VSTM are called “pre-attentive visual features”. If you do not make use of VSTM the brain must send the visual information to another area of the brain for more robust processing, but this additional processing is considerably slower than VSTM.
- 19. How many 5s are there? Answering this question must be done consciously, or “attentively”. ◦ We can process it attentively either using linguistic skills (find the number 5s), or ◦ We can process it attentively using pattern matching skills (find things shaped like ‘5’) Either of these options require “attentive” processing.
- 20. Try again… How many 5s are there? Answering the question now can be done subconsciously, or “pre-attentively”. We took advantage of a VSTM pre-attentive feature called “color hue”. This technique is known as “perceptual popout” and is often implemented as a “highlight” in visualization tools.
- 21. Have our sales increased or decreased over the four years? Which category has grown the fastest? This cannot be processed pre-attentively as text and math require post- attentive processing.
- 22. Have our sales increased or decreased over the four years? Which category has grown the fastest? This can be processed pre-attentively.
- 23. Data Visualization Best Practices Webinar
- 24. Form ◦ Line orientation ◦ Line length ◦ Line width ◦ Size ◦ Enclosure ◦ Shape ◦ Curvature ◦ Concave / Convex Color ◦ Hue ◦ Intensity Position ◦ 2D position ◦ Stereoscopic depth Motion ◦ Flicker ◦ Direction of motion ◦ Velocity
- 39. Data Visualization Best Practices Webinar
- 40. Categorical Data – Data that logically belongs to a group based on characteristics. ◦ North America, Europe, Asia ◦ Eric, Sheri, John ◦ Pizza, Twinkies, potato chips Ordinal Data – Data that logically belongs to a group based on characteristics, but also has a logical sequence to group members: ◦ Gold, Silver, Bronze ◦ Doctoral, Masters, Bachelors ◦ May, June, July
- 41. Quantitative Data – Data that defines “how much” of something there is. ◦ Sales: $10,000; $1 million; $4 billion ◦ SAT scores: 1100, 1500, 2400 ◦ Fertility rate: 1.8, 2.4, 7.6 ◦ Temperature: -26 ℃, 20 ℃, 46 ℃
- 42. After decades of scientific research the best combination of pre-attentive approach for each type of data have been identified:
- 43. Data Visualization Best Practices Webinar
- 44. Follow a methodology Define the central question Know the audience Determine “next steps” to support Classify the deliverable Profile data Apply the most effective visual features Design iteratively
- 45. Define a process by which you: ◦ Obtain design requirements ◦ Access source data ◦ Design visuals ◦ Release and promote Having a methodology allows you to continuously improve and achieve consistent quality in your deliverables. Checklists and/or forms are very helpful. Unilytics recommends our UD3 methodology for dashboard design and construction.
- 46. What question should the dashboard answer? Your audience will never clearly interpret your visual if you, as the designer, didn’t clearly define the question to start with. If you don’t know the question you’re answering, how can you answer it? If the “question” you’re answering is a paragraph, you haven’t really simplified and distilled your requirements… a sentence or two should be adequate to express almost any data inquiry. Corollary questions are OK, but keep visuals focused on that main question. If you’re building a visual that is hard to trace back to the central question… it shouldn’t be included.
- 47. Not everyone interprets or understands data the same way you do, or the same other users of the visual will. Are they technical or not? Do they understand statistics? How will they access your visuals? How will they understand KPIs when they look at them? Will they know what to do after getting an answer from your visual?
- 48. Some dashboards present “information only”, while others support further action on the part of your audience (“next steps”). Know which of these you’re creating. If your visual supports further action, know what information your audience will need to perform these actions. Summarize the core information for “next steps” as succinctly as possible in as centralized a location as possible.
- 49. Remember the three main types of analytical visuals, and know which one you’re building: ◦ Strategic/Executive – A regularly updated answer to a question or line of inquiry that frequently monitors operational concerns in response to events or on an ad-hoc basis. ◦ Operational – A high level view of a question or line of inquiry that is usually answered in a routine, specific way and usually presents KPIs in a minimally interactive way. d ◦ Analytical – A highly interactive view that provides a variety of investigative approaches to a specific central topic with a few corollary contextual views.
- 50. Remember that data comes in three flavours: ◦ Categorical – Data that logically belongs together, such as: North America, Europe, and Asia. ◦ Ordinal – Data that logically belongs together and has a logical sequence: gold, silver, and bronze medals. ◦ Quantitative – Data that defines “how much” of something there is: $1 million in sales, 20° Celsius, 150 defects.
- 51. Use the most effective visual feature for your type of data:
- 52. A good way to kill any business intelligence methodology is to force designers to wait for 100% complete requirements. The best way to design is to bring audience representatives or stakeholders in during critical points and show them what is being created. Let the audience representatives and stakeholders do “mid-stream course corrections” as early as possible to ensure minimal lost or “redone” work. Remember, you’re communicating visually… not linguistically. It’s very hard to guarantee you’re “seeing” in your head what the audience is expecting to “see” from their end… so check in with them routinely during design and construction.
- 53. Follow a methodology Define the central question Know the audience Determine “next steps” to support Classify the deliverable Profile data Apply the most effective visual features Design iteratively