A Quote by Kurt Bollacker

Data that is loved tends to survive. — © Kurt Bollacker
Data that is loved tends to survive.
If you want data to survive, carve it in rock.
We just kind of relied on written scouting reports through the eighties and even the early nineties. I've really been amazed by some of the data that's out there, especially with regards to tendencies of hitters, and certainly tendencies of pitchers as well. I would have loved to have gotten that data when I played.
The biggest mistake is an over-reliance on data. Managers will say if there are no data they can take no action. However, data only exist about the past. By the time data become conclusive, it is too late to take actions based on those conclusions.
The strong live and the weak die. There is some bloodshed, and out of it emerges a much leaner industry, which tends to survive.
One of the myths about the Internet of Things is that companies have all the data they need, but their real challenge is making sense of it. In reality, the cost of collecting some kinds of data remains too high, the quality of the data isn't always good enough, and it remains difficult to integrate multiple data sources.
A data scientist is that unique blend of skills that can both unlock the insights of data and tell a fantastic story via the data.
I do not use airplanes. They strike me as unsporting. You can have an automobile accident-and survive. You can be on a sinking ship-and survive. You can be in an earthquake, fire, volcanic eruption, tornado, what you will-and survive. But if your plane crashes, you do not survive. And I say the heck with it.
Data!data!data!" he cried impatiently. "I can't make bricks without clay.
Go out and collect data and, instead of having the answer, just look at the data and see if the data tells you anything. When we're allowed to do this with companies, it's almost magical.
I have always loved solitude, a trait which tends to increase with age.
Biases and blind spots exist in big data as much as they do in individual perceptions and experiences. Yet there is a problematic belief that bigger data is always better data and that correlation is as good as causation.
Any time scientists disagree, it's because we have insufficient data. Then we can agree on what kind of data to get; we get the data; and the data solves the problem. Either I'm right, or you're right, or we're both wrong. And we move on. That kind of conflict resolution does not exist in politics or religion.
People think 'big data' avoids the problem of discrimination because you are dealing with big data sets, but, in fact, big data is being used for more and more precise forms of discrimination - a form of data redlining.
In my view, our approach to global warming exemplifies everything that is wrong with our approach to the environment. We are basing our decisions on speculation, not evidence. Proponents are pressing their views with more PR than scientific data. Indeed, we have allowed the whole issue to be politicized-red vs blue, Republican vs Democrat. This is in my view absurd. Data aren't political. Data are data. Politics leads you in the direction of a belief. Data, if you follow them, lead you to truth.
If you have a loved one, you can survive anything.
Scientific data are not taken for museum purposes; they are taken as a basis for doing something. If nothing is to be done with the data, then there is no use in collecting any. The ultimate purpose of taking data is to provide a basis for action or a recommendation for action. The step intermediate between the collection of data and the action is prediction.
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