Big Data // Big Data Analytics
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1/3/2014
09:06 AM
Noah Iliinsky
Noah Iliinsky
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Big Data Visualization: 3 Errors To Avoid

Avoid common visualization mistakes. Here's advice on how to clarify goals and get better results.

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davidallanvan
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davidallanvan,
User Rank: Apprentice
1/8/2014 | 4:16:18 AM
Re: Keep-It-Simple Principle Rules
Tips are useful when they help people avoid making some common mistakes, and this article includes some good ones. But tips-based approaches take shortcuts that bypass a rock-solid understanding of fundamental principles. In Data Visualization, those principles are clearly and comprehensively explained by Edward Tufte in his book, The Visual Display of Quantitative Information. His grounding assumption is that statististicians lack an understanding of graphics, and graphic artists don't understand statistics. It is unlikely that one can present statistics well without understanding the fundamentals, just like it is unlikely that urban planners can be successful without understanding the work of William H. Whyte.
Laurianne
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Laurianne,
User Rank: Author
1/3/2014 | 12:43:08 PM
Smart question to ask
I'm really glad the author made this point, asking: "What decisions do you need to inform (and what are we going to do about it)?"

Does the data help people make the decision at hand? And can your data experts grasp the nuances of the decision? This is another example of why having data science/analytics  experts from varying backgrounds proves valuable.
D. Henschen
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D. Henschen,
User Rank: Author
1/3/2014 | 10:26:21 AM
Keep-It-Simple Principle Rules
I subscribe to the Stephen Few school in believing that good data visualizations are simple, clear visualizations. Noah has it right that showing two much information and using overly complicated formats is a rookie mistake. Avoid extraneous eye candy, like 3D effects and coloration without meaning. For more on effective visualization, check out our "Top 15 Data Visualization Tips."
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