Quotes on Data

In God we trust; all others bring data.

Good science is all about following the data as it shows up and letting yourself be proven wrong, and letting everything change while you're working on it - and I think writing is the same way.

The clarity was startling and Samson wondered whether he was imagining these moments. Not that they hadn't happened at all, but that they had been embellished by details from elsewhere, fragments that survived the obliteration of other memories, vagrant data that gravitated and stuck to what was left to remember. But in the end he rejected this idea. The memories were too perfect: take one detail away and they collapsed into disorder.

I wonder whether any other generation has seen such astounding revolutions of data and values as those through which we have lived. Scarcely anything material or established which I was brought up to believe was permanent and vital, has lasted. Everything I was sure or taught to be sure was impossible, has happened.

Without the hard little bits of marble which are called 'facts' or 'data' one cannot compose a mosaic; what matters, however, are not so much the individual bits, but the successive patterns into which you arrange them, then break them up and rearrange them.

In a single sentence the moral is: admit that complexity always increases, first from the model you fit to the data, thence to the model you use to think about and plan about the experiment and its analysis, and thence to the true situation.

I had ... come to an entirely erroneous conclusion, which shows, my dear Watson, how dangerous it always is to reason from insufficient data.

Our business is not based on having information about you. You’re not our product. Our product are these, and this watch, and Macs and so forth. And so we run a very different company. I think everyone has to ask, how do companies make their money? Follow the money. And if they’re making money mainly by collecting gobs of personal data, I think you have a right to be worried.

If you go back back a few hundred years, what we take for granted today would seem like magic - being able to talk to people over long distances, to transmit images, flying, accessing vast amounts of data like an oracle. These are all things that would have been considered magic a few hundred years ago.

Data is like garbage. You'd better know what you are going to do with it before you collect it.

With the Internet, the greatest disseminator of bad data and bad information the universe has ever known, it's become impossible to trust any news from any source at all, because it's filtered through this crazy yenta gossip line. It's impossible to know anything.

Don't be buffaloed by experts and elites. Experts often possess more data than judgment. Elites can become so inbred that they produce hemophiliacs who bleed to death as soon as they are nicked by the real world.

Data is a lot like humans: It is born. Matures. Gets married to other data, _x000D_ divorced. Gets old. One thing that it doesn't do is die. It has to be killed.

The chief problem in historical honesty is not outright lying. It is omission or de-emphasis of important data. The definition of 'important', of course, depends on one's values.

Although each of us obviously inhabits a separate physical body, the laboratory data from a hundred years of parapsychology research strongly indicate that there is no separation in consciousness.

Without big data analytics, companies are blind and deaf, wandering out onto the Web like deer on a freeway.

Maybe stories are just data with a soul.

I will, in fact, claim that the difference between a bad programmer and a good one is whether he considers his code or his data structures more important. Bad programmers worry about the code. Good programmers worry about data structures and their relationships.

Paleontologists [fossil experts] have paid an exorbitant price for Darwin's argument. We fancy ourselves as the only true students of life's history, yet to preserve our favored account of evolution by natural selection we view our data as so bad that we almost never see the very process we profess to study.

Why don't I talk about Big Data? Because I am focused on intelligent answers and not speeds and feeds. It doesn't matter if it is quick if it's the wrong answer.

Confusion and clutter are failures of design, not attributes of information. And so the point is to find design strategies that reveal detail and complexity - rather than to fault the data for an excess of complication. Or, worse, to fault viewers for a lack of understanding.