Top 1200 Data Centers Quotes & Sayings - Page 4

Google is famous for making the tiniest changes to pixel locations based on the data it accrues through its tests. Google will always choose a spartan webpage that converts over a beautiful page that doesn't have the data to back it up.

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.

The librarian isn't a clerk who happens to work in a library. A librarian is a data hound, a guide, a sherpa and a teacher. The librarian is the interface between reams of data and the untrained but motivated user.

What I tend to do is blend quantitative with the qualitative to allow me to plot the qualitative data in some way. It's a question of what quantitative data are most applicable. So I'm playing with that, merging the two.

We charted individual pitches by hand, so I had that data from game to game, but from year to year, I didn't really have that data, because a lot of times it was discarded.

'Data exhaust' is probably my least favorite phrase in the big data world 'cause it sounds like something you're trying to get rid of or something noxious that comes out of the back of your car.

I wonder what really goes on in the minds of Church leadership who know of the data concerning the Book of Abraham, the new data on the First Vision, etc.... It would tend to devastate the Church if a top leader were to announce the facts.

Our problems are not with the data, itself, but arise from our interpretation of the data.

The big thing that's happened is, in the time since the Affordable Care Act has been going on, our medical science has been advancing. We have now genomic data. We have the power of big data about what your living patterns are, what's happening in your body. Even your smartphone can collect data about your walking or your pulse or other things that could be incredibly meaningful in being able to predict whether you have disease coming in the future and help avert those problems.

Apple knows a lot of data. Facebook knows a lot of data. Amazon knows a lot of data. Microsoft used to, and still does with some people, but in the newer world, Microsoft knows less and less about me. Xbox still knows a lot about people who play games. But those are the big five, I guess.

What's going on in the game today... it's data vs. art - that's what it comes down to for me. Art being the human heartbeat, data being numbers, the math, etc. I believe there's a balance to be struck right there.

In C there are no data structures: there are pointers and pointer arithmetic. So you have a pointer into a data structure.

I am what we call a 'karma yogi' in Sanskrit. A karma yogi is somebody who believes in data. I collect a lot of data.

Every company has big data in its future and every company will eventually be in the data business.

So much of the physical world has been explored. But the deluge of data I get to investigate really lets me chart new territory. Genetic data from people living today forms an archaeological record of what happened to their ancestors 10,000 years ago.

Integral to the orb is our low cost long-range wireless radio data system and a protocol that allows us to send this data over 90% of the US population every 15 minutes throughout the day.

Machine learning and artificial intelligence applications are proving to be especially useful in the ocean, where there is both so much data - big surfaces, deep depths - and not enough data - it is too expensive and not necessarily useful to collect samples of any kind from all over.

We tend to assume that data is either private or public, either owned by one person or shared by many. In fact there's more to it than that, above and beyond the upsetting reality that private data is now anything but.

I would only have been too pleased if someone had asked me for my data. If you really believed in your data, you wouldn't mind someone looking at it. You should be able to respond that if you don't believe me go out and do the measurements yourself.

By using big data, it will also be possible to predict adverse weather conditions, rerouting ships to avoid delays, and monitor fuel data, thereby allowing companies to optimize their supply chains and the way they drive their business.

The NSA is not listening to anyone's phone calls. They're not reading any Americans' e-mails. They're collecting simply the data that your phone company already has, and which you don't have a reasonable expectation of privacy, so they can search that data quickly in the event of a terrorist plot.

The whole enterprise of teaching managers is steeped in the ethic of data-driven analytical support. The problem is, the data is only available about the past. So the way we've taught managers to make decisions and consultants to analyze problems condemns them to taking action when it's too late.

A scientist naturally and inevitably ... mulls over the data and guesses at a solution. He proceeds to testing of the guess by new data-predicting the consequences of the guess and then dispassionately inquiring whether or not the predictions are verified.

I am a data hound and so I usually end up working on whatever things I can find good data on. The rise of Internet commerce completely altered the amount of information you could gather on company behavior so I naturally drifted toward it.

In the increasingly digital world, data is a valuable currency, yet as consumers, we control and own little of it. As consumers, we must ask what big companies do with our data, a question directed to both the online and traditional ones.

While I'm driving, I've got speed, gear, lap time, water temperature, blood sugar, RPM, oil pressure. I've got car data and body data all together. It's all on the dash.

I think I've read all of W.E.B. Du Bois, which is a lot. He started off with comprehensive field work in Philadelphia, publishing a book in 1899 called 'The Philadelphia Negro'. It was this wonderful combination of clear statistical data and ethnographic data.

I think philosophers can do things akin to theoretical scientists, in that, having read about empirical data, they too can think of what hypotheses and theories might account for that data. So there's a continuity between philosophy and science in that way.

The conjuror or con man is a very good provider of information. He supplies lots of data, by inference or direct statement, but it's false data. Scientists aren't used to that scenario. An electron or a galaxy is not capricious, nor deceptive; but a human can be either or both.

Any enterprise CEO really ought to be able to ask a question that involves connecting data across the organization, be able to run a company effectively, and especially to be able to respond to unexpected events. Most organizations are missing this ability to connect all the data together.

... while in theory digital technology entails the flawless replication of data, its actual use in contemporary society is characterized by the loss of data, degradation, and noise; the noise which is even stronger than that of traditional photography.

I think the first wave of deep learning progress was mainly big companies with a ton of data training very large neural networks, right? So if you want to build a speech recognition system, train it on 100,000 hours of data.

Data is just like crude. It’s valuable, but if unrefined it cannot really be used. It has to be changed into gas, plastic, chemicals, etc to create a valuable entity that drives profitable activity; so must data be broken down, analyzed for it to have value.

Sense data are much more controversial than qualia, because they are associated with a controversial theory of perception - that one perceives the world by perceiving one's sense-data, or something like that.

We should have companies required to get the consent of individuals before collecting their data, and we should have as individuals the right to know what's happening to our data and whether it's being transferred.

Part of my responsibility as an officer was to oversee a team of analysts charged with synthesizing all of the data points on the map to see how one related to another. By bringing those data points together, a broader picture could be drawn and a strategy developed to counter the existing threat.

The paradigm shift of the ImageNet thinking is that while a lot of people are paying attention to models, let's pay attention to data. Data will redefine how we think about models.

Facts and data, rather than opinion, are the two cornerstones of problem solving, and yet they are consistently withheld from the people by American media. We must have facts and data in order to recognize where there is a problem!

The biggest challenge in big data today is asking the right questions of data. There are so many questions to ask that you don't have the time to ask them all, so it doesn't even make sense to think about where to start your analysis.

Data is the new soil, because for me, it feels like a fertile, creative medium. Over the years, online, we've laid down a huge amount of information and data, and we irrigate it with networks and connectivity, and it's been worked and tilled by unpaid workers and governments.

Many of us now expect our online activities to be recorded and analyzed, but we assume the physical spaces we inhabit are different. The data broker industry doesn't see it that way. To them, even the act of walking down the street is a legitimate data set to be captured, catalogued, and exploited.

I visit T-Mobile call centers. We've got about 18 major call centers in the US, and before I was CEO, I heard that no CEO had gone to physically visit them. I go in, they meet me outside, we take selfies as I stand like a piece of furniture, I tell them about how things are going - but most importantly, I say thank you and help them see that their behavior and their work has driven the culture of the company that's changed the industry and the whole world. It's a bit of a love affair.

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.

Centralization of society's vital services in giant computer centers, reservoirs, nuclear power plants, air- traffic control centers, 100-story skyscrapers, and government compounds increases its vulnerability. ... choosing his targets, today's saboteur could pollute a city's water supply, dynamite power transmission towers, cripple an airport control center, destroy a corporate or government computer center.

The bigger a data set that you have, the more polls, the more surveys that you have that people undertake, the more accurate your models are going to be. That's just a fact of data science.

We are now at a point in time when the ability to receive, utilize, store, transform and transmit data - the lowest cognitive form - has expanded literally beyond comprehension. Understanding and wisdom are largely forgotten as we struggle under an avalanche of data and information.

My job is to analyze our data set to understand it and build products on it. I look at raw data, do the math to clean it up, and build systems to make it easy to understand.

I'm repledging myself to human-scale values. As a fiction writer, the best data comes through the senses and is then processed through many revisions. We have to learn to be intelligent assessors of the data coming in to us and what it's doing to our mental process.

I don't think bulk data collection was an enormous factor here, because generally, that deals with overseas calls to the United States. But what bulk data collection did was make the process more efficient. So there were no silver bullets there.

I kept a notebook, a surreptitious journal in which I jotted down phrases, technical data, miscellaneous information, names, dates, places, telephone numbers, thoughts, and a collection of other data I thought was necessary or might prove helpful.

A great deal of creativity is about pattern recognition, and what you need to discern patterns is tons of data. Your mind collects that data by taking note of random details and anomalies easily seen every day: quirks and changes that, eventually, add up to insights.

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.

Data is very important, but you have to be good at reading the data in an emotional way. If you look at a selling report, there's an emotional trend to what's selling.

When you have a large amount of data that is labeled so a computer knows what it means, and you have a large amount of computing power, and you're trying to find patterns in that data, we've found that deep learning is unbeatable.

Users get unlimited 'WhatsApp'. We get happy users who don't have to worry about data. Carriers get people willing to sign up for data plans.

I tend to write poetry that is rich in data of various sorts. The lyric poem isn't perfectly suited to accommodating such data, so I've had to find new ways to say everything that I want to say.

It is for these reasons that I believe we must expand day-care centers and provide other assistance which I have recommended to the Congress. At present, the total facilities of all the licensed day-care centers in the Nation can take care of only 185,000 children. Nearly 500,000 children under 12 must take care of themselves while their mothers work. This, it seems to me, is a formula for disaster.

Converting Facebook data into money is harder than it sounds, mostly because the vast bulk of your user data is worthless. Turns out your blotto-drunk party pics and flirty co-worker messages have no commercial value whatsoever.

Concepts are vindicated by the constant accrual of data and independent verification of data. No prize, not even a Nobel Prize, can make something true that is not true.

National data on evictions aren't collected, although national data on foreclosures are. And so if anyone wants to, kind of, get to know any statistical research about evictions, they have to really dig in the annals of legal records.