Top 1200 Data Centers Quotes & Sayings

I'm going to say something rather controversial. Big data, as people understand it today, is just a bigger version of small data. Fundamentally, what we're doing with data has not changed; there's just more of it.

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.

If I never see you again I will always carry you inside outside on my fingertips and at brain edges and in centers centers of what I am of what remains.

TIA was being used by real users, working on real data - foreign data. Data where privacy is not an issue.

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.

[Sovereignty] would break the American monopoly, but it would also break Internet business, because you'd have to have a data center in every country. And data centers are tremendously expensive, a big capital investment.

Before, companies and startups had to lay up all this capital for data centers and servers, and take your scarce resource, which in most companies is engineers, and have them work on the undifferentiated heavy lifting of infrastructure. What the cloud has done is completely flipped that model on its head so that you only pay for what you consume.

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 USA Freedom Act does not propose that we abandon any and all efforts to analyze telephone data, what we're talking about here is a program that currently contemplates the collection of all data just as a routine matter and the aggregation of all that data in one database. That causes concerns for a lot of people... There's a lot of potential for abuse.

MapReduce has become the assembly language for big data processing, and SnapReduce employs sophisticated techniques to compile SnapLogic data integration pipelines into this new big data target language. Applying everything we know about the two worlds of integration and Hadoop, we built our technology to directly fit MapReduce, making the process of connectivity and large scale data integration seamless and simple.

Big data is great when you want to verify and quantify small data - as big data is all about seeking a correlation - small data about seeking the causation.

The vast majority of companies will not own their own data centers in the fullness of time. All that computing is moving to the cloud. This space is going to be a high-volume, relatively low-margin business.

Facebook collects a lot of data from people and admits it. And it also collects data which isn't admitted. And Google does too. As for Microsoft, I don't know. But I do know that Windows has features that send data about the user.

Citizens must pressure the American Hospital Association, the American Public Health Association, the Centers for Disease Control and other relevant governmental agencies to make greening our hospitals and medical centers a top priority so that they themselves don't create even more illness.

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.

Data!data!data!" he cried impatiently. "I can't make bricks without clay.

When dealing with data, scientists have often struggled to account for the risks and harms using it might inflict. One primary concern has been privacy - the disclosure of sensitive data about individuals, either directly to the public or indirectly from anonymised data sets through computational processes of re-identification.

We use nearly 5 thousand different data points about you to craft and target a message. The data points are not just a representative model of you. The data points are about you, specifically.

You have to imagine a world in which there's this abundance of data, with all of these connected devices generating tons and tons of data. And you're able to reason over the data with new computer science and make your product and service better. What does your business look like then? That's the question every CEO should be asking.

Centers of unionism are also the centers of unemployment.

With too little data, you won't be able to make any conclusions that you trust. With loads of data you will find relationships that aren't real... Big data isn't about bits, it's about talent.

The absolute awareness only comes when you become the Spirit. When you get your realization and you become the Spirit. When you are the Spirit, then what happens that you start feeling on your central nervous the centers of all the people who are around you and your own centers.

They're trying to put data centers in cold environments because they're actually generating so much heat now; they're using up so much electricity.

I used to collect computer punch cards from the data centers.

In Google data centers, our energy usage throughout the year for all our computing needs is 100 percent renewable.

It's no secret that COVID-19 has impacted immigration detention centers at an alarming rate. We must establish accountability and transparency in reporting data to ensure detention centers are taking the necessary precautions to protect detained individuals.

Government alone cannot solve the problems we deal with in our correctional facilities, treatment centers, homeless shelters and crisis centers - we need our faith-based and community partners.

An artist will starve unless he is near big centers of population. We should create many of these cultural centers right in our own slums.

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 will talk about two sets of things. One is how productivity and collaboration are reinventing the nature of work, and how this will be very important for the global economy. And two, data. In other words, the profound impact of digital technology that stems from data and the data feedback loop.

I think Unix is a great system - especially for running data centers - because it is very mature, very reliable, very scalable. But when I want to go out and populate small devices, I think Java.

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.

I love the academy in terms of the life of the mind and the world of ideas. I also love the streets. I love the churches and mosques and synagogues. I love the trade union centers. I love the community centers. I speak regularly at prisons and so forth.

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.

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.

We are ... led to a somewhat vague distinction between what we may call "hard" data and "soft" data. This distinction is a matter of degree, and must not be pressed; but if not taken too seriously it may help to make the situation clear. I mean by "hard" data those which resist the solvent influence of critical reflection, and by "soft" data those which, under the operation of this process, become to our minds more or less doubtful.

I was interested in data mining, which means analyzing large amounts of data, discovering patterns and trends. At the same time, Larry started downloading the Web, which turns out to be the most interesting data you can possibly mine.

Data dominates. If you've chosen the right data structures and organized things well, the algorithms will almost always be self-evident. Data structures, not algorithms, are central to programming.

The data set of proxies of past climate used in Mann...for the estimation of temperature from 1400 to 1980 contains collation errors, unjustifiable truncation or extrapolation of source data, obsolete data, geographical location errors, incorrect calculation of principal components and other quality control defects.

I know that Boston is one of the great centers of intellectual culture as well as sport. It's one of the centers of America, with a great orchestra, great sports, great hospitals, and great universities.

There's a lot of power in executing data - generating data and executing data.

Every company has messy data, and even the best of AI companies are not fully satisfied with their data. If you have data, it is probably a good idea to get an AI team to have a look at it and give feedback. This can develop into a positive feedback loop for both the IT and AI teams in any company.

I don't believe in data-driven anything, it's the most stupid phrase. Data should always serve people, people should never serve data.

The first wave of the Internet was really about data transport. And we didn't worry much about how much power we were consuming, how much cooling requirements were needed in the data centers, how big the data center is in terms of real estate. Those were almost afterthoughts.

Personal computing today is a rich ecosystem encompassing massive PC-based data centers, notebook and Tablet PCs, handheld devices, and smart cell phones. It has expanded from the desktop and the data center to wherever people need it - at their desks, in a meeting, on the road or even in the air.

Wikipedia was offline after an overheating problem at one of its data centers. It was pretty bad. For a while there, people had nowhere to go for phony, inaccurate information.

We'd realized in the first ten years we'd built an infrastructure competence deep in the stack - reliable, scalable cost effective data centers to grow the Amazon retail biz the way we needed to. But we'd built Amazon so quickly that a number of the pieces of the platform had become entangled.

The Centers for Disease Control (CDC) reports that the number of overweight adult Americans increased over 60 percent between 1991 and 2000. According to CDC data, the U.S. population of overweight children between ages two and five increased by almost 36 percent from 1989 to 1999.

New laboratories and centers will help our schools lift their standards of excellence and explore new methods of teaching. These centers will provide special training for those who need and deserve special treatment.

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.

The expansion of tobacco cessation centers is an important part of our historic and continuing effort to help smokers quit. The expansion of these centers will give even more New Yorkers the help they need to quit once and for all.

I'm kind of fascinated by this idea that we can surround ourselves with information: we can just pile up data after data after data and arm ourselves with facts and yet still not be able to answer the questions that we have.

People believe the best way to learn from the data is to have a hypothesis and then go check it, but the data is so complex that someone who is working with a data set will not know the most significant things to ask. That's a huge problem.

There was really interesting work going on, for example, in the Mississippi bayou, where there were some really exemplary health centers that also became centers with kind of political organizing.

These seven centers, these seven chakras Yoga and Tantra have talked about down the ages, are nothing but five knots in your body electric current. They can be changed; they can be rearranged. They can be given a new shape, form. Two lovers can be transformed so deeply that all their seven centers can start meeting.

Tape with LTFS has several advantages over the other external storage devices it would typically be compared to. First, tape has been designed from Day 1 to be an offline device and to sit on a shelf. An LTFS-formatted LTO-6 tape can store 2.5 TB of uncompressed data and almost 6 TB with compression. That means many data centers could fit their entire data set into a small FedEx box. With LTFS the sending and receiving data centers no longer need to be running the same application to access the data on the tape.

But look what we have built low-income projects that become worse centers of delinquency, vandalism and general social hopelessness than the slums they were supposed to replace. Cultural centers that are unable to support a good bookstore. Civic centers that are avoided by everyone but bums. Promenades that go from no place to nowhere and have no promenaders. Expressways that eviscerate great cities. This is not the rebuilding of cities. This is the sacking of cities.

We all say data is the next white oil. [Owning the oil field is not as important as owning the refinery because what will make the big money is in refining the oil. Same goes with data, and making sure you extract the real value out of the data.]

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.

We get more data about people than any other data company gets about people, about anything - and it's not even close. We're looking at what you know, what you don't know, how you learn best. The big difference between us and other big data companies is that we're not ever marketing your data to a third party for any reason.