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Visual Business Intelligence

Visual Business Intelligence
We typically think of quantitative scales as linear, with equal quantities from one labeled value to the next. For example, a quantitative scale ranging from 0 to 1000 might be subdivided into equal intervals of 100 each. Linear scales seem natural to us. Logarithms and their scales are quite useful in mathematics and at times in data analysis, but they are only useful for presenting data on those relatively rare cases when addressing an audience that consists of those who have been trained to think in logarithms. For my own analytical purposes, I use logarithmic scales primarily for a single task: to compare rates of change. I decided to write this blog piece when I ran across the following graph in Steven Pinker’s new book Enlightenment Now: The darkest line, which represents the worldwide distribution of per capita income in 2015, is highlighted as the star of this graph. Why didn’t Pinker use a linear scale? This provides a cozy sense of bell-shaped equity, which isn’t truthful. Related:  Data VisualizationsInfoVis

The Functional Art Well-formed data Gun Deaths In America This interactive graphic is part of our project exploring the more than 33,000 annual gun deaths in America and what it would take to bring that number down. See our stories on suicides among middle-age men, homicides of young black men and accidental deaths, or explore the menu for more coverage. Methodology The data in this interactive graphic comes primarily from the Centers for Disease Control and Prevention’s Multiple Cause of Death database, which is derived from death certificates from all 50 states and the District of Columbia and is widely considered the most comprehensive estimate of firearm deaths. In keeping with the CDC’s practice, deaths of non-U.S. residents that take place in the U.S. The “homicides” category includes deaths by both assault and legal intervention (primarily shootings by police officers). For shootings of police officers, we used the FBI’s count of law enforcement officers “feloniously killed” by firearms in the line of duty.

Data Underload Most Common Occupation by Age As we get older, job options shift — along with experience, education, and wear on our bodies. Waiting For a Table A simulation to estimate how long until you are seated at a restaurant. How Different Income Groups Spend Money After living expenses, where does the money go, and how does it change when you have more cash available? The Demographics of Others I think we can all benefit from knowing a little more about others these days. Constructed Career Paths from Job Switching Data Shifting from one occupation to another can take a swing in the career path. Switching Jobs When people move to different jobs, here's where they go. Percentage of People Who Married, Given Your Age Or, given your age, the percentage of fish left in the sea. American Daily Routine Sleep. In 2017, No More than Five Days Without a Mass Shooting Unfortunately, while of varying magnitude, mass shootings are somewhat regular in the United States. Who Earns More Income in American Households?

Duarte Blog Just a couple more stops until the Death Star. @sean_voegeli Many of our employees live a long way from the office. One of our designers has a particularly hellish trek. Instead of whining about it — or just staring at his phone like the rest of us — he started making it a #creativecommute. Sean Voegeli* is a talented illustrator, avid Instagrammer, and loyal Star Wars fan. First, where can we find your work? What tools do you use? I like Adobe Draw a lot. How has your #creativecommute affected your day? On the way home, it’s a good way to unwind and transition into dad-mode. How do you decide what to draw? Which comes first, illustration or photo? How long does each piece take to make? Why Instagram? Do you have a favorite piece? “All strollers and droids must enter through the gate please.” And this one. Don’t you dare order a hotdog at this Disneyland stand. Last question, who should we be following on Instagram? So we dare you.

One Dataset, Visualized 25 Ways “Let the data speak.” It’s a common saying for chart design. The premise — strip out the bits that don’t help patterns in your data emerge — is fine, but people often misinterpret the mantra to mean that they should make a stripped down chart and let the data take it from there. You have to guide the conversation though. You must help the data focus and get to the point. To show you what I mean, I present you with twenty-five charts below, all based on the same dataset. Click images for the full size charts. Looks like spaghetti Shows countries separately so that lines don’t overlap No surprises Shows change over time with bars, would probably benefit from sorting Focus on the the difference between the two sexes, with comparison across countries Focus on difference between male and female over time A focus the change between two time periods instead of the fluctuations Comparison between the two, in a more compact space Shows changes over time, although not super clear with this dataset Focus

Best of the visualization web At the end of each month I pull together a collection of links to some of the most relevant, interesting or thought-provoking web content I've come across during the previous month. Here's the latest collection from January 2018. Visualisations & Infographics Includes static and interactive visualisation examples, infographics and galleries/collections of relevant imagery. SRF | 'Roger Federer: 20 Years, 20 Titles' Mapping Police Violence | '2017 Police Violence Report... collected data on over 1,100 killings by police in 2017.' SCMP | '2017: the safest skies record' SCMP | ... and here's a photo of the print version Economics | 'All the president’s tweets' Pixel Mixer | 'Anatomy of a Viz - The Level is in the Details' Mike Vizneros | 'A Chamber Divided: What We Can Learn By Using BioFabric Charts' Taylor Baldwin | 'Audiofabric' Guardian | 'Bussed out: How America moves its homeless' Twitter | 'A climate change cross stitch' Guardian | 'How the NHS winter beds crisis is hitting patient care'

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IEEE VIS 2017 Chart Porn Presentation Zen How We Use Data to Inspire Design – Design x Data – Medium By Arianna McClain & Rohini Vibha When most people imagine good design, numbers probably don’t come to mind. In fact, anything quantitative might feel completely at odds with the concept of beautiful design. But at IDEO, in addition to connecting with people and learning their stories, designers use quantitative data as a tool to gain empathy and inspiration. We learn from numbers the same way we learn from people, because we see numbers as a representation of people. In our traditional human-centered design process, we empathize by going where people live and work. How might we use quantitative data to inspire design? Talk to extreme users If we wanted to learn how to improve a product, would it be better to talk to someone who feels indifferent towards the product or someone who hates it? Quantitative data is perfect for helping designers determine who the extreme users are to better understand what makes them stand out. Immerse yourself in people’s lives

FiveThirtyEight Why the London of British Literature Barely Changed for 200 Years Erik Steiner is a geographer, and in his field people trying to understand how places worked in the past tend to look at census records and old maps. But in a recent project, Steiner, the creative director of Stanford University’s Spatial History Project, worked with colleagues from the school’s Literary Lab to mine an unusual source of geographical data: 4,862 works of British literature, published between 1700 and 1900. “From a geographer’s standpoint, fictional geography is amazing,” he says. In the case of London, one of the team’s discoveries, published in a pamphlet this past fall, was that the physical London of the 19th century and the fictional London of the same time period occupied two different geographic spaces. “From the perspective of literature, London’s urban development didn’t quite happen,” says Ryan Heuser, a Stanford graduate student who led the Literary Lab’s research on the project. With that data set in hand, the researchers worked to map literary London.

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