Category Archives: Stephen Few

Stephen Few: Now You See It

Portland

Readers:

Stephen_Few2I was in Portland, Oregon last week attending three data visualization workshops by industry expert, Stephen Few. I was very excited to be sitting at the foot of the master for three days and soak in all of this great dataviz information.

Last Thursday, was the third workshop, Now You See It which is based on Steve’s best-selling book (see photo below).

To not give away too much of what Steve is teaching in the workshops, I have decided to discuss one of our workshop topics, human perceptual and cognitive strengths.

You can find future workshops by Steve on his website, Perceptual Edge.

Best Regards,

Michael

Now You See It

 

Designed for Humans

Good visualizations and good visualization tools are carefully designed to take advantage of human perceptual and cognitive strengths and to augment human abilities that are weak. If the goal is to count the number of circles, this visualization isn’t well designed. It is difficult to remember what you have and have not counted.

Quickly, tell me how many blue circles you see below.

Design for Humans 1

The visualization below, shows the same number of circles, however, is well designed for the counting task. Because the circles are grouped into small sets of five each, it is easy to remember which groups have and have not been counted, easy to quickly count the number of circles in each group, and easy to discover with little effort that each of the five groups contains the same number of circles (i.e., five), resulting in a total count of 25 circles.

Design for Humans 2

The arrangement below is even better yet.

Design for Humans 3

Information visualization makes possible an ideal balance between unconscious perceptual and conscious cognitive processes. With the proper tools, we can shift much of the analytical process from conscious processes in the brain to pre-attentive processes of visual perception, letting our eyes do what they do extremely well.

Stephen Few: Information Dashboard Design

Readers:

Stephen_Few2I am in Portland, Oregon this week attending three data visualization workshops by industry expert, Stephen Few. I am very excited to be sitting at the foot of the master for three days and soak in all of this great dataviz information.

Today, was the second workshop, Information Dashboard Design which is based on Steve’s best-selling book (see photo below).

To not give away too much of what Steve is teaching in the workshops, I have decided to discuss one of the dashboard exercises we did in class. The goal here was to find what we feel is wrong with the dashboard.

I will show you the dashboard first. Then, you can see our critique below.

You can find future workshops by Steve on his website, Perceptual Edge.

Best Regards,

Michael

Information Dashboard Design

 

Dashboard To Critique

CORDA Airlines Dashboard

Critique Key Points

  • Top left chart – Only left hand corner chart has anything to do with flight loading
  • Top left chart – are flight numbers useful?
  • Two Expand/Print buttons – Need more clarity (right-click on chart would be a better choice)
  • Top right chart – Poor use of pie charts – size of pies are telling largest sales channel – use small multiple bar charts, total sales as a fourth bar chart
  • Redundant use of “February” – In the title and in charts
  • Bottom left chart – why does it have a pie chart in it?
  • Bottom right chart  – map may be better as a bar chart (geographical display could be useful if we had more information). Current way bubbles are being expressed is not useful (use % cancellations instead). Symbols may have a different meaning every day
  • Bottom right chart – CORDAir Logo – is this necessary?
  • Location of drop-down. Not clear if it applies to top left chart or all charts
  • Backgrounds – heavy colors, gradients
  • Instructions should be in a separate help document. Only need to learn this once.
  • Top left chart: Faint Image in background. Suppose to look like a flight seating map. Do you really want to see this every day? It is a visual distraction.
  • IMPORTANT: Is there visual context offered with any of the graphs? No. This is critical.

————————————————————————————————-

Dashboard Example Source: Website of Corda Technologies Incorporated, which has since been acquired by Domo.

Stephen Few: Show Me The Numbers

Readers:

Stephen_Few2I am in Portland, Oregon this week attending three data visualization workshops by industry expert, Stephen Few. I am very excited to be sitting at the foot of the master for three days and soak in all of this great dataviz information.

Yesterday, was the first workshop, Show Me the Numbers which is based on Steve’s best-selling book (see photo below).

To not give away too much of what Steve is teaching in the workshops, I have decided for today to show a “before and after” example with Steve’s explanation of why he made the changes he did.

You can find future workshops by Steve on his website, Perceptual Edge.

Best Regards,

Michael

Show Me the Numbers

 

“Before” Example

In the example below, the message contained in the titles is not clearly displayed in the graphs. The message deals with the ratio of indirect to total sales – how it is declining domestically, while holding steady internationally. You’d have to work hard to get this message the display as it is currently designed.

Before - Show Me the Numbers

 

“After” Example

The revised example below, however, is designed very specifically to display the intended message. Because this graph, is skillfully designed to communicate, its message is crystal clear. A key feature that makes this so is the choice of percentage for the quantitative scale, rather than dollars.

After - Show Me the Numbers

Additional Thoughts From Steve

The type of graph that is selected and the way it’s designed also have great impact on the message that is communicated. By simply switching from a line graph to a bar graph, the decrease in job satisfaction among those without college degrees in their later years is no longer as obvious.

More Thoughts - Show Me the Numbers

Infographic: Mount Hood, Portland, Oregon (Ben VanderVeen)

Readers:

Stephen_Few2I am in Portland, Oregon this week attending three data visualization classes by industry expert, Stephen Few. I am very excited to be sitting at the foot of the master for three days and soak in all of this great dataviz information.

Ben VanderveenTo follow my theme of highlighting cities I visit, I found an inforgraphic created by Ben VanderVeen of Mount Hood. Ben is a filmmaker and designer living on the west coast. On his website you will find examples of his design work, video projects, documentary film and more. If you are interested in hiring Ben for a project or working collaboratively, visit his contact page here.

Stay tune for highlights of each of the three classes by Stephen Few over the next few days.

Best Regards,

Michael

 

MtHood1024

Stephen Few: Why Do We Visualize Quantitative Data?

Readers:

Stephen_FewIt has been a while since I have discussed some of the latest creative thoughts on data visualization from Stephen Few. I have read all of Steve’s books, attended several classes from him,  and religiously follow his blog and newsletter on his website, Perceptual Edge.

For those of you who don’t know, Stephen Few is the Founder & Principal of Perceptual Edge. Perceptual Edge, founded in 2003, is a consultancy that was established to help organizations learn to design simple information displays for effective analysis and communication.

Steve has stated that his company will probably always be a company of one or two people, which is the perfect size for him. With 25 years of experience as an innovator, consultant, and educator in the fields of business intelligence and information design, he is now considered the leading expert in data visualization for data sense-making and communication.

Steve writes a quarterly Visual Business Intelligence Newsletter, speaks and teaches internationally, and provides design consulting. In 2004, he wrote the first comprehensive and practical guide to business graphics entitled Show Me the Numbers, now in its second edition. In 2006, he wrote the first and only guide to the visual design of dashboards, entitled Information Dashboard Design, also now in its second edition. In 2009, he wrote the first introduction for non-statisticians to visual data analysis, entitled Now You See It.

Here is his latest thoughts from his newsletter.

Best regards,

Michael

 

Why Do We Visualize Quantitative Data?

Per Stephen Few, we visualize quantitative data to perform three fundamental tasks in an effort to achieve three essential goals:

Web

These three tasks are so fundamental to data visualization, Steve used them to define the term, as follows:

Data visualization is the use of visual representations to explore, make sense of, and communicate data.

Steve poses the question of why is it that we must sometimes use graphical displays to perform these tasks rather than other forms of representation? Why not always express values as numbers in tables? Why express them visually rather than audibly?

Essentially, there is only one good reason to express quantitative data visually: some features of quantitative data can be best perceived and understood, and some quantitative tasks can be best performed, when values are displayed graphically. This is so because of the ways our brains work. Vision is by far our dominant sense. We have evolved to perform many data sensing and processing tasks visually. This has been so since the days of our earliest ancestors who survived and learned to thrive on the African savannah. What visual perception evolved to do especially well, it can do faster and better than the conscious thinking parts of our brains. Data exploration, sensemaking, and communication should always involve an intimate collaboration between seeing and thinking (i.e., visual thinking).

Despite this essential reason for visualizing data, people often do it for reasons that are misguided. Steve dispels a few common myths about data visualization.

Myth #1: We visualize data because some people are visual learners.

While it is true that some people have greater visual thinking abilities than others and that some people have a greater interest in images than others, all people with normal perceptual abilities are predominantly visual. Everyone benefits from data visualization, whether they consider themselves visual learners or not, including those who prefer numbers.

Myth #2: We visualize data for people who have difficulty understanding numbers.

While it is true that some people are more comfortable with quantitative concepts and mathematics than others, even the brightest mathematicians benefit from seeing quantitative information displayed visually. Data visualization is not a dumbed-down expression of quantitative concepts.

Myth #3: We visualize data to grab people’s attention with eye-catching but inevitably less informative displays.

Visualizations don’t need to be dumbed down to be engaging. It isn’t necessary to sacrifice content in lieu of appearance. Data can always be displayed in ways that are optimally informative, pleasing to the eye, and engaging. To engage with a data display without being well-informed of something useful is a waste.

Myth #4: The best data visualizers are those who have been trained in graphic arts.

While training in graphic arts can be useful, it is much more important to understand the data and be trained in visual thinking and communication. Graphic arts training that focuses on marketing (i.e., persuading people to buy or do something through manipulation) and artistry rather than communication can actually get in the way of effective data visualization.

Myth #5: Graphics provide the best means of telling stories contained in data.

While it is true that graphics are often useful and sometimes even essential for data-based storytelling, it isn’t storytelling itself that demands graphics. Much of storytelling is best expressed in words and numbers rather than images. Graphics are useful for storytelling because some features of data are best understood by our brains when they’re presented visually.

We visualize data because the human brain can perceive particular quantitative features and perform particular quantitative tasks most effectively when the data is expressed graphically. Visual data processing provides optimal support for the following:

1. Seeing the big picture

Graphs reveal the big picture: an overview of a data set. An overview summarizes the data’s essential characteristics, from which we can discern what’s routine vs. exceptional.

The series of three bar graphs below provides an overview of the opinions that 15 countries had about America in 2004, not long after the events of 9/11 and the military campaigns that followed.

graph-of-country-opinions

Steve first discovered this information in the following form on the website of PBS:

table-of-country-opinions

Based on this table of numbers, he had to read each value one at a time and, because working memory is limited to three or four simultaneous chunks of information at a time, he couldn’t use this display to construct and hold an overview of these countries’ opinions in his head. To solve this problem, he redisplayed this information as the three bar graphs shown above, which provided the overview that he wanted. Steve was able to use it to quickly get a sense of these countries’ opinions overall and in comparison to one another.

Bonus: Here is a link to where Steve discusses the example above on his website.

2. Easily and rapidly comparing values

Try to quickly compare the magnitudes of values using a table of numbers, such as the one shown above. You can’t, because numbers must be read one at a time and only two numbers can be compared at a time. Graphs, however, such as the bar graphs above, make it possible to see all of the values at once and to easily and rapidly compare them.

3. Seeing patterns among values

Many quantitative messages are revealed in patterns formed by sets of values. These patterns describe the nature of change through time, how values are distributed, and correlations, to name a few.

Try to construct the pattern of monthly change in either domestic or international sales for the entire year using the table below.

table-of-sales-data

Difficult, isn’t it? The line graph below, however, presents the patterns of change in a way that can be perceived immediately, without conscious effort.

graph-of-sales-data

You can thank processes that take place in your visual cortex for this. The visual cortex perceives patterns and then the conscious thinking parts of our brains make sense of them.

4. Comparing patterns

Visual representations of patterns are easy to compare. Not only can the independent patterns of domestic and international sales be easily perceived by viewing the graph above, but they can also be compared to one another to determine how they are similar and different.

In Summary

These four quantitative features and activities require visual displays. This is why we visualize quantitative data.

Critiquing Data Visualizations

Jeff PettirossCritiquing Data Visualizations

I attended an online webinar today hosted by Data Science Central titled Making Flow Happen: Dashboards that Persuade, Inform, and Engage. The presenter was Jeff Pettiross (photo, right) from Tableau Software. I found Jeff’s presentation to be very informative and helpful, but it was the Q&A session afterwards that I thought brought an interesting topic to the surface.

The question asked was:

When creating a dataviz and taking feedback, how do you determine what feedback is based on personal opinion and what feedback adds flow to your dataviz?

Jeff discussed this as having principal-centered arguments versus personal-centered arguments. So, for principal-centered arguments, you could refer to Edward Tufte when you are discussing the field of data visualization, junk charts or small multiples, Stephen Few for best practices for dashboard design, or Alberto Cairo for best practices for creating infographics. You could also discuss articles and academic research related to data visualization.

Where the water gets murky is when you are exposed to personal-centered arguments or, basically, someone’s personal opinion. Sometimes when you are sitting in a dataviz review session, the criticism or critiques you receive can feel very personal. Some of it may be in the way the person is expressing their opinion and the intonation in their voice. Other times it truly may be personal; that personal may not like the person being reviewed or feels threatened by their work.

Jeff made a real good suggestion related to personal critiques by simply asking more questions. Deflect the criticism and ask them to tell you more about what they did not like about the visualization. For example, they might feel your dashboard is too crowded or too busy. You might want to ask for suggestions from that person. If the situation allows, you could bring up a copy of that visualization and make the changes in real-time as they are stating their suggestions.

Jeff pointed out that, unfortunately, this will not work in all cases. If you are a paid consultant at a company, and the client insists that they want it a particular way, the old motto “The Customer is Always Right” would take precedence here. You could say, “O.K., we will do it this way this time, but I would like you to consider this as an alternative for future visualizations.”

Jeff pointed out that at Tableau, they are a critique-centric culture. They often have review sessions of their visualizations where people from different areas of the company may sit in. For example, you might have Sales people, consultants, marketing, training, etc.  Using thoughtful critiques, spending about 20 minutes on each feature, and including a diverse group of people, they are able to refine the dataviz as a group and learn and hear other people’s ideas on dataviz.

Thanks to Jeff and Data Science Central for a great session today. What do you think? What do you feel is the best way to critique data visualizations?

I would love to hear your thoughts.

Best Regards,

Michael

Stephen Few on Data Visualization and the Blind

Note: I was supposed to have attended Stephen Few’s three data visualization classes this week in Portland, but preparations for a client presentation in Paris next week made attending impossible.

Dashboard Insight posted a synopsis of a post Stephen did on Data Visualization and the Blind. My wife has worked in Special Education for over 39 years and I feel this is a very important topic as we become more of a visual society. I am including the synopsis from Dashboard Insight which also has a link to the full post on Stephen’s Perceptual Edge Website.

One “6 degrees” side note. Stephen mentions in his article that he received an e-mail from Mark Ostroff which motivated his blog on this topic. I knew Mark many years ago. Mark was (and probably still is) the definitive guru on all things Hyperion. I actually went to the Hyperion World Conference one year in Chicago and attended several of Mark’s sessions. A very innovative and passionate speaker.

I will be doing some Paris/France themed data visualization blogs over the next week or so. So stay tuned and laissez le bon temps rouler.

Best regards,

Michael

Software-For-Visually-Impaired-Blind-Users

Dashboard Insight had posted an article on data presentation for the blind a couple of weeks ago. There was little information out there on how to handle it and what measures there are for translating information displayed within data visualization or a dashboard to the blind. When Stephen Few posted on this subject a couple of days ago we were quite excited.

Stephen_Few“I’ll begin by stating my fundamental position: a dashboard that is accessible to the blind is a contradiction in terms. “A dashboard 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” (Few, 2005). No forms of data visualization, not just dashboards jam-packed with graphics, can be made fully accessible to someone who is blind. I am not insensitive to the needs of people who are visually or otherwise impaired. I am merely pointing out what anyone who understands data visualization knows: no channel of perception other than vision can fully duplicate the contents of graphs. Similarly, what someone can communicate through the audio channel in the form of music cannot be fully expressed visually. If it could, why bother performing or recording music? Why not just distribute the written score? Vision is unique in its abilities to inform and enable thinking. Those who lack vision can develop their other senses to compensate to an amazing degree, but never in a way that fully duplicates the visual experience.”

“The information that is displayed in a dashboard can and should be presented to people who are blind in a different form when needed… Unfortunately, an alternative form of presentation will not convey all of the information contained in a well-designed dashboard and it won’t communicate the information as efficiently, but if someone who is blind needs the information, it behooves us to provide a reasonable, even if imperfect, alternative. The alternative, however, will not be a dashboard. By definition, a dashboard is a visual display, because the visual channel provides the richest and most efficient means of presenting information for monitoring purposes, which no other channel can match—not even close. If airlines were required by law to provide flight-phobic customers with an earthbound form of transportation, that alternative would be called a train or a bus, not an airplane. In like manner, a means of monitoring that uses braille or a screen reader as its medium should not be called a dashboard. There’s enough confusion about the term already. Let’s not muddy it further.”

It is an insightful and educational read we recommend. You can find the full article here.

Stephen Few’s New Book: Information Dashboard Design: Displaying Data for At-a-Glance Monitoring, Second Edition

Information Dashboard Design: Displaying data for at-a-glance monitoring, Second Edition, Stephen Few, $40.00 (U.S.), Analytics Press, 2013

Stephen_FewThe second edition of Stephen Few’s seminal book, Information Dashboard Design, will be released on August 15, 2013. I have been waiting for this book for some time and am very excited about its pending release.

Here is a description of the book from Amazon.com:

A leader in the field of data visualization, Stephen Few exposes the common problems in dashboard design and describes its best practices in great detail and with a multitude of examples in this updated second edition. According to the author, dashboards have become a popular means to present critical information at a glance, yet few do so effectively. He purports that when designed well, dashboards engage the power of visual perception to communicate a dense collection of information efficiently and with exceptional clarity and that visual design skills that address the unique challenges of dashboards are not intuitive but rather learned. The book not only teaches how to design dashboards but also gives a deep understanding of the concepts—rooted in brain science—that explain the why behind the how. This revised edition offers six new chapters with sections that focus on fundamental considerations while assessing requirements, in-depth instruction in the design of bullet graphs and sparklines, and critical steps to follow during the design process. Examples of graphics and dashboards have been updated throughout, including additional samples of well-designed dashboards.

Since I have not seen a copy of the book yet, here are some reviews from Alberto Cairo and others reviewers:

Don’t be misled by the title. This is not just a book about information dashboards, but arguably the most concise and information-dense treaty on how to present quantitative information by means of graphics. Among the many people who are currently writing about data visualization and infographics, Stephen Few is one of a kind, someone who can translate huge amounts of research in statistics, visual perception, cognition, and business intelligence into practical guidelines. Information Dashboard Design is, in this sense, a perfect blend of theory and practice.
 
Alberto Cairo, author of The Functional Art
  
Stephen Few is evidently a man of taste and wisdom. This volume speaks eloquently about common pitfalls and the path that avoids them. He performs a tremendous service of assimilating work by other greats and adding useful innovations of his own. If you appreciate great design and work with numbers, this will make you a hero. Rarely do you acquire expensive new skills as easily as you will by reading this book.
 
Skip Savage (from an Amazon.com review)
  
If you want a performance dashboard that helps you truly manage performance (and not just pretend to), read this book first. Then buy a copy for your dashboard developer, or hire a developer that already practices its principles.
 
Stacey Barr, The Performance Measure Specialist
  
The most powerful designs are the ones we do not notice. The real power of designers and developers is in turning something incredibly complex into something amazingly simple. The challenge is not to add new features but to add value and power to products without adding any complexity. Design does not happen by accident. It is the product of careful and deliberate planning. Stephen Few demonstrates this through examples and best practices that are easy to understand and will improve how we display information. Businesses that value design will leap ahead because they will able to quickly assimilate information, efficiently focus time and efforts, and create alignment, agility and effectiveness. This book provides a running head start!
 
Eleanor Taylor, Strategist, SAS Institute

I look forward to the book and will provide an in-depth review once I read it. I am looking forward to reading about Stephen’s analysis of his dashboard contest he held last summer. Also, Stephen has introduced a few new visualizations I look forward to reading about and implementing in my bag of tricks.

Stay tuned.

Regards,

Michael

Stephen Few’s Review of Tableau 8: Tableau Veers from the Path

The first person who exposed me to best practices in data visualization was Stephen Few. I had the good fortune to take a one day Data Visualization class from him in 2007 at TDWI in San Diego. Stephen’s company is called Stephen Few, Perceptual EdgePerceptual Edge.

Stephen founded Perceptual Edge as a consultancy that was established to help organizations learn to design simple information displays for effective analysis and communication. With 25 years of experience as an innovator, consultant, and educator in the fields of business intelligence and information design, Stephen is now a leading expert in data visualization for data sense-making and communication.

He writes a quarterly Visual Business Intelligence Newsletter, speaks and teaches internationally, and provides design consulting.  In 2004, he wrote the first comprehensive and practical guide to business graphics entitled Show Me the Numbers, in 2006, he wrote the first and only guide to the visual design of dashboards, entitled Information Dashboard Design, and in 2009 he wrote the first introduction for non-statisticians to visual data analysis, entitled Now You See It.

With that introduction to Stephen Few, I wanted to provide you a link to his web site and his review of Tableau 8. Here is a brief snippet of Stephen’s review.

“I’ve seen it happen many times, but it never ceases to sadden me. An organization starts off with a clear vision and an impervious commitment to excellence, but as it grows, the vision blurs and excellence gets diluted through a series of compromises. Software companies are often founded by a few people with a great idea, and their beginnings are magical. They shine as beacons, lighting the way, but as they grow, what was once clear becomes clouded, what was once firm becomes flaccid, and what was once promising becomes just one more example of business as usual.”

Regards,

Michael

Review: MOOC Course, Introduction to Infographics and Data Visualization

alberto_cairo_post

Alberto Cairo

I have now completed my MOOC course, Introduction to Infographics and Data Visualization, taught by Alberto Cairo. I wanted to write a review so future students of this class know what to expect. I tried to break down my review by topic.

Signing up

I first found out about the course by visiting Mr. Cairo’s Website, http://thefunctionalart.com, after I had purchased his book to read. I had tried to sign up for the first session of this course taught last year, but it filled up very quickly. I went on full alert to make sure I was able to sign up for the second offering which started last January. Even with a cap of 5,000 students, the class filled quickly, but I was quick and able to enroll.

Communication

Mr. Cairo started each week by sending us an e-mail “New message from Alberto Cairo” which had a few notes and a link to the course News and
Announcements forum. In the forum, Mr. Cairo posted detailed instructions for the week along with any recommendations and insights into the assignment. Between Mr. Cairo and Rachel Barrera, his Graduate Assistant for the class, I received e-mails every few days to let us know what the expectations were, informational items, etc. I felt the communication level was just right and both of them answered e-mail questions in a very timely manner.

Lectures

Lecture 1

Lecture 1

The lectures were all taught from video. The MOOC philosophy is to keep lectures around 12 minutes or less in length, which works out to about five videos to watch per hour lecture. The reasoning behind this is that our attention span starts to lapse after 15 minutes, so if the class is broken down into smaller chunks, we are more inclined to watch a shorter session on a particular topic as well as retain the information better. For the first week of class, Mr. Cairo’s videos were 2:32 minutes, 6:17 minutes, 12:03 minutes, 8:04 minutes, 9:51 minutes, 14:20 minutes, and 5:35 minutes. His style of lecture is to tell you a story related to the topic. I found the individual lectures very informative, interesting and the time went by very quickly when watching them.

Reading

Mr. Cairo gave us a lot of different materials for reading. For example, in the second week of the course, we were assigned the following:

1. Read the interviews with John Grimwade (Condé Nast Traveler) and Steve Duenes/Xaquín GV (The New York Times).

2. Read Data Visualization for Human Perception, by Stephen Few.

Also, each week, Mr. Cairo would provide us links to additional articles, videos, and blogs he put together. They were optional, but again very useful. He also sent us an e-mail each week of links to other interesting materials to read.

Discussion

Each week, we were required to participate in the discussion forums. Whether it was to post our opinion on a topic or review other classmates assignments, we had to post 2-3 entries each week. At first, I did not think I would like this, but found this to be one of the most enjoyable parts of the class. When reviewing other classmate’s projects and assignments, we had 5,000 different examples to choose from, so there should have been discussions that appealed to everyone. I was very fortunate since the ones I picked were very interesting to read. Since we had a large pool of people from many different walks of life, we had a lot of diversity in why they created the design they did, their personal or professional interest in that topic, and the actual visualization they produced often gave me ideas for projects I was working on at work. Even after I finished my mandatory 2-3 entries to review, I often went back and read others I thought were of interest. For the final assignment we were able to pick our own topic. I frequented the discussion forum a lot just to see the variety of topics and infographics my classmates created. I was a bit frustrated that time did not permit me to view them all.

Quizzes

We had two quizzes early in the class. If you read the materials and watched the lectures, you will have no problem with these.

Projects/Assignments

We had three projects to complete as part of the class. The first was to create a topical interactive graphic. The second was to create a visualization, and the third project was to create an infographic.

I put a lot of time into these projects. I was fortunate in that I was able to tie my third project into a need we had at work for an infographic. So, not only was I learning, but I was able to promote the use of infographics at work.

For the second assignment, I really liked the visualization created by one of my classmates I will refer to as “Jim.” I liked it so much in fact, that I wanted to make a working example for our development team at work. I create a lot of dashboard “templates” for our development team in MicroStrategy, which is our enterprise standard BI tool.

So, using Jim’s data and format, I created a dashboard in MicroStrategy with some tweaks to it.

I have included a screenshot of my assignment on this project below.

I used horizontal stacked bar charts instead so that the viewer can visually see how social security and income tax rate add up to the total and explains visually why the countries are ordered the way they are on the dashboard. I also separated out $100K and $300K percentages into separate visuals.

In addition, I added the flags of the countries. Yes, I know, chart junk!

Now, you don’t see any numbers on the data points in this dashboard. The reason you don’t see them is because they appear when you mouse over a bar where you then see the country, category and the percent value as a tooltip.

I don’t know Jim but want to thank him for providing a great example for me to follow. This will help our team a lot in creating future dashboards.

An Exploration of Tax Data

[Click on the image above to enlarge]

Best Quote

“Christmas cards do not cause Christmas to happen, but the two are highly correlated in time.”

Summary

I know there is a lot of discussion about MOOCs and if they adequately provide a viable learning device right now. I feel a MOOC is really no different from any University course I took when I was in college. You will get out of a MOOC course what you are willing to put into it. I took this course very seriously and set my getting the Certificate of Completion as my goal. To get this, I had to do all of the course work. This class was something I wanted to take to enhance my skills as well as my career. I also took this course because I had read Mr. Cairo’s book, The Functional Art, and wanted to learn more from him. In regards to the readings, I was fortunate that I had already read most of Mr. Cairo’s book and had previously read many of the articles he assigned, such as Stephen Few’s material, so the reading assignments were not as steeped for me. However, I did go out and read a lot of the supplemental materials that I found of interest too.

The lectures were excellent and some were down right fascinating. I loved how Mr. Cairo told the story about John Snow and the 1854 Cholera Epidemic in London. I also loved the story and explanation of how we interpret circles and why not to use them in data visualizations.

When Mr. Cairo offers his third version of this class, I highly recommend you take it if you have the opportunity (sign up early!) I find myself longing for more and hope Mr. Cairo or his counterparts like Stephen Few, Nigel Holmes, Colin Ware or Edward Tufte offer similar MOOC courses.

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