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FCW : September 15, 2013
Bookshelf What not to do with your data The federal government has long produced data by the truckload, and the open-data initiatives of the Obama administration have put more of it in the public eye than ever before. And although many agencies have moved beyond spreadsheets and CSV les to offer dashboards, maps and other visualization tools, the vast major- ity of those presentations are not very good. Nathan Yau is trying to change that. His book, "Data Points: Visu- alization that Means Something," does not focus on agencies in particular, though federal data is discussed and used in dozens of sample charts and graphs. Wheth- er it is census data or a chart com- paring the cost of cable television vs. Net ix and other "cord-cutting" options, the challenge remains the same: how to make a visual pre- sentation clear enough to be easily comprehensible, yet informative enough to tease out real insights. Effective visualization is hard, Yau stresses, and requires a mix of math and design skills that few individuals possess. "Data Points" is not a technical how-to guide --- though Yau has written that, too, with his 2011 book "Visualize This." His goal this time is to walk would-be data visualizers through the process of design and analysis, from the ground rules of statistics and visual aesthetics to proven best practices for storytelling and com- mon errors to avoid. Want to know whether to use a pie chart or a bar chart for a par- ticular dataset, and what signals a map s color palette sends to the audience? "Data Points" has the answers. Curious about how to explore and display the correlation between two variables? Yau plots education data from all 50 states 18 ways and shows how different visuals can uncover very different patterns in a single dataset. With a mix of hard rules, best- practice examples, and data-visu- alization history that dates back to William Playfair and Florence Nightingale, Yau seeks to impart a mindset as much as a skill set. "The mark of a good graph is not only how fast you can read it," he writes, quoting statistician William Cleveland, "but also what it shows. Does it enable you to see what you could not see before?" Kaiser Fung s new book, mean- while, dispenses with the aes- thetic visual storytelling questions entirely, instead drilling into the dangers of datasets themselves. In "Numbersense: Using Big Data to Your Advantage," Fung warns that "people in industry who wax on about Big Data take it for granted that more data begets more good.... [But] when more people are per- forming more analyses more quick- ly, there are more theories, more points of view, more complexity, more con icts and more confusion. There is less clarity, less consensus and less con dence." Two new books help map the danger zones of data visualization --- and of the datasets themselves BY TROY K. SCHNEIDER Bookshelf September 15, 2013 FCW.COM 31 A common mistake is that all visualization must be simple, but this skips a step. You should actually design graphics that lend clarity, and that clarity can make a chart 'simple to read.
August 30, 2013
September 30, 2013