Data Quotes
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We need a data network that can easily carry voice, instead of what we have today, a voice network struggling to carry data.
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This flight was an engineer's dream. We are collecting so much data. We are looking at several different types of sensors. We are doing things we never imagined we would be able to do.
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When you read findings like the one above, and see that Jamal doesn’t get the job, it’s easy to shake your head at the few racist hiring managers who’ve tilted the odds against him. But the data we see in this chapter shows racism isn’t a problem of outliers. It is pervasive.
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In the future, I think movies are going to be more of data sets that viewers have a hand in controlling - where the narrative originates and what happens to the content.
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The public trusts big data way too much.
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Uncontrolled access to data, with no audit trail of activity and no oversight would be going too far. This applies to both commercial and government use of data about people.
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It is a capital mistake to theorize before one has data. Insensibly one begins to twist facts to suit theories, instead of theories to suit facts.
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In God we trust, everybody else bring data to the table.
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One of the best things data can enable us to do is to ask questions we didn't know to ask.
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Don't measure anything unless the data helps you make a better decision or change your actions. If you're not prepared to change your diet or your workouts, don't get on the scale.
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There is no data that can be displayed in a pie chart, that cannot be displayed BETTER in some other type of chart.
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My answer to someone who is in contrast with me - by not seeing God in the scientific data - is that you don't see God in the scientific data because you're not me. I have other experiences than you have, that bring me to look at this data as enriching my experience of God.
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The best decision-makers are always armed with the best information and data!
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We discovered that there are actually fewer companies actually buying data.
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Data is not useful until it becomes information.
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We have so much data on the web, almost all of it available for free, that we dive into the the data ocean hoping that magically awesome things will follow. They never do.
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We lisp in numbers, in the U.S. We are deluged by ample, often mysterious statistics. ... Like many in this country, I have come to regard statistics with doubt and merely as a hint of the probable shape of fact.
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If someone does a study which, for statistical reasons, I think is hopelessly underpowered or nonidentified, my best and most useful advice will not be tips on how to calculate p-values better, or how to construct an explanation for some particular data pattern. Rather, my advice will be to start over, to reconsider what you think you already know, maybe to question some prominent work in your subfield, and quite possibly to think a lot harder about measurement, and about the relation of your data to your underlying constructs of interest.
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This is where the world is going: direct access from anywhere to any type of data, whether it's a small piece of data or a small answer but a long algorithm to create that answer. The user doesn't care about this.
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Data is what distinguishes the dilettante from the artist
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I related to the whole hippie, acid-test confluence of the early Internet. The idea that we should be open and interoperate with our data resonated with me.
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But it's not the pressure of data that gives rise to the understanding. It's, on the contrary, the child's own struggle to make sense of the data.
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It might be the first time - certainly the first time in my lifetime that a major policy address by a Republican presidential nominee Donald Trump so heavily relied on data and studies from a labor-union-backed think tank.
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We cannot be guided by wishful thinking. We need objective data.