Quotes on Data

Scientists who think science consists of unprejudiced data-gathering without speculation are merely cows grazing on the pasture of knowledge.

Data is not information, Information is not knowledge, Knowledge is not understanding, Understanding is not wisdom.

We must be careful not to confuse data with the abstractions we use to analyse them.

Now that knowledge is taking the place of capital as the driving force in organizations worldwide, it is all too easy to confuse data with knowledge and information technology with information.

Stairway to Wisdom”) David Brooks detailed the needed ingredients to gaining a deep understanding of a social problem, beginning with the data and moving on to first-hand accounts. The highest rung on his stairway, though, went beyond those: “Empathy opens you up to absorb the good and the bad. Love impels you not just to observe but to seek union—to think as another thinks and feel as another feels.

Science may provide the most useful way to organize empirical, reproducible data, but its power to do so is predicated on its inability to grasp the most central aspects of human life: hope, fear, love, hate, beauty, envy, honor, weakness, striving, suffering, virtue.

People in both fields operate with beliefs and biases. To the extent you can eliminate both and replace them with data, you gain a clear advantage.

My hair would continue to gray, and then one day, it would fall out entirely, and then, on a day meaninglessly close to the present one, meaninglessly like the present one, I would disappear from the earth. And all these emotions, all these yearnings, all these data, if that helps to clinch the enormity of what I'm talking about, would be gone. And that's what immortality means. It means selfishness. My generations belief that each one of us matters more than you or anyone else would think.

Great wisdom not applied to action and behavior is meaningless data.

Don't measure anything unless the data helps you make a better decision or change your actions. _x000D_ _x000D_ If you're not prepared to change your diet or your workouts, don't get on the scale.

[N]o scientist likes to be criticized. ... But you don't reply to critics: "Wait a minute, wait a minute; this is a really good idea. I'm very fond of it. It's done you no harm. Please don't attack it." That's not the way it goes. The hard but just rule is that if the ideas don't work, you must throw them away. Don't waste any neurons on what doesn't work. Devote those neurons to new ideas that better explain the data. Valid criticism is doing you a favor.

We have three approaches at our disposal: the observation of nature, reflection, and experimentation. Observation serves to assemble the data, reflection to synthesise them and experimentation to test the results of the synthesis. The observation of nature must be assiduous, just as reflection must be profound, and experimentation accurate. These three approaches are rarely found together, which explains why creative geniuses are so rare.

Endless data show that diverse teams make better decisions. We are building products that people with very diverse backgrounds use, and I think we all want our company makeup to reflect the makeup of the people who use our products. That's not true of any industry really, and we have a long way to go.

What I think is coming instead are much more organic ways of organizing information than our current categorization schemes allow, based on two units - the link, which can point to anything, and the tag, which is a way of attaching labels to links. The strategy of tagging - free-form labeling, without regard to categorical constraints - seems like a recipe for disaster, but as the Web has shown us, you can extract a surprising amount of value from big messy data sets.

We want to build systems that can generalize to a new task. Being able to do things with much less data and with much less computation is going to be interesting and important.

Here I shall add that the concept of change, and with it the concept of motion, as change of place, is possible only through and in the representation of time. & Motion, for example, presupposes the perception of something movable. But space considered in itself contains nothing movable; consequently motion must be something which is found in space only through experience -in other words, is an empirical datum.

A graphic representation of data abstracted from the banks of every computer in the human system. Unthinkable complexity. Lines of light ranged in the nonspace of the mind, clusters and constellations of data. Like city lights, receding.

Regardless of what the naysayers believe about human interaction and social media, the data show us that the abundance of technology is actually increasing the abundance of happiness all over the world.

Making good judgments when one has complete data, facts, and knowledge is not leadership - it's bookkeeping

As we move into an era in which personal devices are seen as proxies for public needs, we run the risk that already-existing inequities will be further entrenched. Thus, with every big data set, we need to ask which people are excluded. Which places are less visible? What happens if you live in the shadow of big data sets?

Bosses and leaders everywhere should cherish the people who bring them bad news, disappointing data or hard problems.