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@ -54,6 +54,13 @@ A good visualization will show you things you did not expect or raise new questi
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A good visualization might also hint that you're asking the wrong question or that you need to collect different data.
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Visualizations can surprise you, and they don't scale particularly well because they require a human to interpret them.
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**Models** are complementary tools to visualization.
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Once you have made your questions sufficiently precise, you can use a model to answer them.
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Models are a fundamentally mathematical or computational tool, so they generally scale well.
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Even when they don\'t, it\'s usually cheaper to buy more computers than it is to buy more brains!
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But every model makes assumptions, and by its very nature a model cannot question its own assumptions.
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That means a model cannot fundamentally surprise you.
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The last step of data science is **communication**, an absolutely critical part of any data analysis project.
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It doesn't matter how well your models and visualization have led you to understand the data unless you can also communicate your results to others.
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