Best 902 quotes in «data quotes» category

We're in this period where we're getting good data rates. I would say we're getting data rates that are like the data rates we got when we launched RealAudio in 1995.

We're long past having to defend or explain why women should be on boards, given all the data that shows how companies with female as well as male directors perform better. It's unfortunate when companies with a large percentage of women constituents don't reflect that in their boardrooms.

We're not policy people and we don't want to be policy people. All we're interested in, as social scientists, is data that accurately represents reality.

We're putting more carbon into the atmosphere than the atmosphere can absorb. And everybody told us when we started, coz we knew nothing when we started - we still don't know very much - but everybody told us 'this is crazy, you don't use a scientific data point, it's a number, people don't respond to numbers'.

We're rapidly entering a world where everything can be monitored and measured. But the big problem is going to be the ability of humans to use, analyze and make sense of the data.

We're still missing about a dozen vaccines that will make a huge difference. For adults, we've got HIV and TB are still huge; for kids malaria is still killing a half million kids a year out of that 6 million. We probably need some vaccines, but we need a little more data to make sure we're getting the vaccines that will save the most lives.

We're so obsessed with [big] data, we forget how to interpret it.

We shall see that the mathematical treatment of the subject [of electricity] has been greatly developed by writers who express themselves in terms of the 'Two Fluids' theory. Their results, however, have been deduced entirely from data which can be proved by experiment, and which must therefore be true, whether we adopt the theory of two fluids or not. The experimental verification of the mathematical results therefore is no evidence for or against the peculiar doctrines of this theory.

We should teach the students, as well as executives, how to conduct experiments, how to examine data, and how to use these tools to make better decisions.

We used to be calorie poor and now the problem is obesity. We used to be data poor, now the problem is data obesity.

We've had such thorough training, we've had an excellent team on the ground. With the minor glitches that have occurred, we've been able to take care of them. And the teams on the ground are getting tons of incredible data.

We've seen a lot of data at YC now, and the most successful companies and the ones where the investors do the best... end up giving a lot of stock out to employees- year after year after year.

We will have to become 'perpetual marketers', to learn to be channel and data planners without losing our human insight or creativity; to vastly increase the level of accountability and provide more relevant experiences for customers.

We will ultimately live in a perpetual data-driven talent edition. Everything you create will be measured and tracked by others through comments, share, and likes. Your work will come up on the radar of potential employers and clients, and the data will tell them if you are worth talking to or hiring.

What data can tell you is if you have 10 messages, all of which you believe, it can tell you which messages are resonating and which aren't. And if you break it down even further, the truth of the matter is some messages resonate one place and other messages resonate another place.

Whatever lies beyond the limits of experience, and claims another origin than that of induction and deduction from established data, is illegitimate.

What, exactly, is the internet? Basically it is a global network exchanging digitized data in such a way that any computer, anywhere, that is equipped with a device called a 'modem', can make a noise like a duck choking on a kazoo

What if instead of seeing a neighborhood that reminds you of the place you grew up in, you see your actual neighborhood? The data exists. The technology exists. It's just a matter of sourcing it and processing it in a compelling fashion.

What got repressed-sometimes viciously repressed-by the strategy-concept makers, consultants, and data gatherers was a consciousness of people and their importance in the creation and execution of any strategy.

What I saw during the Hillary Clinton campaign [2016] with data dummies who were more concerned with polls than people, they were more concerned with donors than voters. And it wasn't a lot of heart felt on that campaign and I think it left us vulnerable.

What we did is important because we proved that virtually all of the wireless networks used by companies and hospitals are completely open and offer no protection for the data on them.

What is clear is that users own their data and should have control of how their data is used.

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.

What's needed now are software technologies that interconnect computing systems, people and data to produce more rapid answers to the questions of science, and to help researchers use computation in the most effective manner.

What we have is a data glut.

What we know is smartphones are everywhere and they are rich in data. What we know is that there are apps once downloaded by the consumer that will also in turn download the consumers' contact book. Most consumers don't want that to happen and don't know it's happening.

What we call our data are really our own constructions of other people’s constructions of what they and their compatriots are up to.

When a manager asks for hard data, that's usually just his way of saying no.

When a human being becomes a set of data on a website like Facebook, he or she is reduced. Everything shrinks. Individual character. Friendships. Language. Sensibility.

When future generations look back on the global-warming scare of the past 30 years, nothing will shock them more than the extent to which the official temperature records – on which the entire panic ultimately rested – were systematically “adjusted” to show the Earth as having warmed much more than the actual data justified.

When an idea comes, spend silent time with it. Remember Keats's idea of Negative Capability and Kipling's advice to "drift, wait and obey". Along with your gathering of hard data, allow yourself also to dream your idea into being.

When an economist says the evidence is "mixed," he or she means that theory says one thing and data says the opposite.

When evaluating a model, at least two broad standards are relevant. One is whether the model is consistent with the data. The other is whether the model is consistent with the 'real world.'

When human judgment and big data intersect there are some funny things that happen

When I was standing there on top of the world, you become so humble, you do not think about breaking records anymore, you do not think about gaining scientific data. The only thing you want is to come back alive

When I first began examining the global-warming scare, I found nothing more puzzling than the way officially approved scientists kept on being shown to have finagled their data, as in that ludicrous "hockey stick" graph, pretending to prove that the world had suddenly become much hotter than at any time in 1,000 years. Any theory needing to rely so consistently on fudging the evidence, I concluded, must be looked on not as science at all, but as simply a rather alarming case study in the aberrations of group psychology.

When it comes to exploring the mind in the framework of cognitive neuroscience, the maximal yield of data comes from integrating what a person experiences - the first person - with what the measurements show - the third person.

When I was working in Japan, I created a system for ensuring that intelligence data was globally recoverable in the event of a disaster. I was not aware of the scope of mass surveillance. I came across some legal questions when I was creating it. My superiors pushed back and were like, "Well, how are we going to deal with this data?" And I was like, "I didn't even know it existed.

When we miss with all the metadata collection we've had, the San Bernardino couple and the Tsarnaev brothers, what that suggests to me is that we are using the wrong algorithms to search through all this data.

When we have all data online it will be great for humanity. It is a prerequisite to solving many problems that humankind faces.

When we share our personal data with business, its use should be transparent and secure.

When you see data, doubt [them]! When you see measurements, doubt them!

When writing gateway software of any kind, take pains to disturb the data stream as little as possible - and never throw away information unless the recipient forces you to!

When you live in a networked environment, it's possible to separate data from applications.

Whether we look at capitalism, taxes, business, or government, the data show a clear and consistent pattern: 70 percent of Americans support the free enterprise system and are unsupportive of big government.

Whereas much of what we know from ancient history is derived from one or two sources, we have no fewer than nine ancient sources, inside and outside the New Testament, corroborating the disciples' conviction that they encountered the resurrected Jesus. That's an avalanche of data.

Where big data is all about seeking correlations - and thus to make incremental changes - small data is all about causations - seeking to understand the reasons why.

While data can only tell you what has happened in the past, it can in some ways give you a sense of what might be of interest to an audience in the future.

Whole communities are growing up without fathers or male role models. Bringing up a family in the best of circumstances is not easy. To try to do it by placing the entire burden on women - 91% of single-parent families in Britain are headed by the mother, according to census data - is practically absurd and morally indefensible.

While it's wonderful that investors have access to all the data now available to them, it has become a full-time job to sift through it and separate out the valuable news from the useless noise.