Best 902 quotes in «data quotes» category

As I noted in my article "Comparing LTO-6 to Scale-Out Storage for Long-Term Retention," in these situations tape is an ideal storage type. Data on tape can still be automatically scanned for durability and it certainly meets the cost-effectiveness requirements.

As somebody who's kind of a technophile, I'm interested in how traditional and digital publishing connect. Maybe ten years ago they were seen as antagonists, but now they complement each other. There's data that shows digital sales actually drive print sales. And even the ways in which pictures and words, text and image, interact - we're seeing these books that are very hard to categorize. All of that is very exciting to me.

As soon as science has emerged from its initial stages, theoretical advances are no longer achieved merely by a process of arrangement. Guided by empirical data, the investigator rather develops a system of thought which, in general, is built up logically from a small number of fundamental assumptions, the so-called axioms. We call such a system of thought a theory. The theory finds the justification for its existence in the fact that it correlates a large number of single observations, and it is just here that the 'truth' of the theory lies.

As the amount of inputs go up, as the number of people and ideas that clamor for attention continue to increase, we do what people always do: we rely on the familiar, the trusted and the personal. The incredible surplus of digital data means that human actions, generosity and sacrifice are more important than they ever were before.

As the data from the past decade clarify, there is no evidence that poverty causes crime but a great deal of evidence that crime causes poverty. By aligning themselves against the police, against commonsense tactics like stop and frisk, against metal detectors in public housing, against swift and certain punishment, and for a broad array of legal protections for accused criminals, liberals helped to aggrieve the lives of the poor and society as a whole.

A technology becomes truly disruptive when it drives the marginal cost of something that used to be scarce and expensive to approach zero. Thus, it used to be to deploy software at scale, you had to fund a data center, buy a set of servers, storage, and networking gear, build an in-house IT management capability, and buy an expensive stack of enabling software before you could even get started. Now you can get all that from Amazon or Microsoft on a pay-as-you-grow model.

A ten per cent reduction in military expenditures per year would be reasonable, coupled with a programme of retraining the workforce and redirecting the resources in a manner that creates employment and advances social welfare. I also encourage all States to contribute to the UN's annual Report on Military Expenditures by submitting complete data on national defence budgets.

A theory with mathematical beauty is more likely to be correct than an ugly one that fits some experimental data.

A theory is only as good as its assumptions. If the premises are false, the theory has no real scientific value. The only scientific criterion for judging the validity of a scientific theory is a confrontation with the data of experience.

At root what is needed for scientific inquiry is just receptivity to data, skill in reasoning, and yearning for truth. Admittedly, ingenuity can help too.

Attempts have been made from a study of the changes produced by mutation to obtain the relative order of the bases within various triplets, but my own view is that these are premature until there is more extensive and more reliable data on the composition of the triplets.

Averages ... seduce us away from minute observation.

A very good friend of mine spent a fair amount of time doing postmortems and met with a number of the senior folks on the Romney campaign and they spent, what was it, $140, $160 million on data. And this friend of mine, who is a very sharp thinker, asked a series of questions, but the most important one he asked, he said, "What decisions did you make differently because of the data?" And he's coming from the private equity world where he wants to know, OK, and the answer from virtually every single senior Romney person was "nothing.

Autobiography. Apparently one should not name the names of those one has been to bed with, or give explicit figures on the amount of money one has earned, those being the two data most eagerly sought by readers; all the rest is legitimate to reveal.

A very small group of powerful people is deciding what's going to happen with your data, and they're using bots to help implement what they want to do. That has nothing to do with democracy. It's all about efficiency. And that's the really scary thing about it.

...a vocal minority of scientists so mistrusts the models and the complex fragmentary data, that some claim that global warming is a hoax. They have made public statements accusing other scientists of deliberate fraud in aid of their research funding. Both sides are now hurling personal epithets at each other, a very bad development in Earth sciences.

Bad programmers worry about the code. Good programmers worry about data structures and their relationships.

Because we're always more woundable when caught at exactly the time where we're in the mood for that particular product or service - and as Big Data increasingly are able to pick up on clues revealing desire - automated systems are increasingly able to hit at exactly those moments, across those channels we move - with an offer matching exactly what we're desiring.

Before anything can be reasoned upon to a conclusion, certain facts, principles, or data, to reason from, must be established, admitted, or denied.

Beware of the problem of testing too many hypotheses; the more you torture the data, the more likely they are to confess, but confessions obtained under duress may not be admissible in the court of scientific opinion.

Belief Systems contradict both science and ordinary "common sense." B.S. contradicts science, because it claims certitude and science can never achieve certitude: it can only say, "This model"- or theory, or interpretation of the data- "fits more of the facts known at this date than any rival model." We can never know if the model will fit the facts that might come to light in the next millennium or even in the next week.

Big data isn’t about bits, it’s about talent.

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.

Big data will never give you big ideas... Big data doesn't facilitate big leaps of the imagination. It will never conjure up a PC revolution or any kind of paradigm shift. And while it might tell you what to aim for, it can't tell you how to get there

Big data is at the foundation of all of the megatrends that are happening today, from social to mobile to the cloud to gaming.

Birth order effects are like those things that you think you see out of the corner of your eye but that disappear when you look at them closely. They do keep turning up but only because people keep looking for them and keep analyzing and reanalyzing their data until they find them.

Big Data will spell the death of customer segmentation and force the marketer to understand each customer as an individual within eighteen months, or risk being left in the dust.

But even if you thought they were adequate at the time, when you're collecting data in bulk-you've got it. The data lasts until you delete it; the rules only last until you decide to change them, and change them in secret.

Both history and contemporary data show that countries prosper more when there are stable and dependable rules, under which people can make investments without having to fear unpredictable new government interventions before these investments can pay off.

Both Newton and Darwin were driven by the data and were forced to recognize that they couldn't explain everything. It may be a characteristic of great scientists to know what to accept and what to leave out.

[Brazil] went to the UN and said, "We need new standards for this." We need to take a look at what they're calling "data sovereignty.

But actually theory is very practical. Gravity is a theory, for example. It allows you to predict that if you step off a cliff you will fall; you don't have to collect data on that.

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

But what I would say to my successor is that it is important not just to shoot but to aim. And it is important, in this seat, to make sure that you're making your best judgments based on data, intelligence, the information that's coming from your commanders and folks on the ground and you're not being swayed by politics.

By analyzing data from Greenwich Observatory in the period 1836-1953, John A. Eddy [Harvard-Smithsonian Center for Astrophysics and High Altitude Observatory in Boulder] and Aram A. Boornazian [mathematician with S. Ross and Co. in Boston] have found evidence that the sun has been contracting about 0.1% per century during that time, corresponding to a shrinkage rate of about 5 feet per hour. And digging deep into historical records, Eddy has found 400-year-old eclipse observations that are consistent with such a shrinkage.

Cloud computing offers individuals access to data and applications from nearly any point of access to the Internet, offers businesses a whole new way to cut costs for technical infrastructure, and offers big computer companies a potentially giant market for hardware and services.

Cancer is really a slew of rare diseases. Lung cancer has 700 sub-types, breast cancer has 30,000 mutations which means that every cancer in its own right is a rare disease. Sharing data globally in this context is really important from a life-threatening perspective.

Cloud storage in data centers will utilize the latest developments in physical storage virtualization, deduplication and other methods to make the most effective use of physical storage assets. Software defined storage could allow a further level of abstraction and cost effectiveness. The vast bulk of content stored "in the cloud" will reside on large SATA interface HDDs with some on magnetic (mostly LTO) tape (particularly for "archives.")

Cats vary so widely that all data is meaningless and the professional classifiers gnash their teeth trying to come up with even a single fact common to all.

Chemistry is necessarily an experimental science: its conclusions are drawn from data, and its principles supported by evidence from facts.

Computer science only indicates the retrospective omnipotence of our technologies. In other words, an infinite capacity to process data (but only data -- i.e. the already given) and in no sense a new vision. With that science, we are entering an era of exhaustivity, which is also an era of exhaustion.

Companies that actually survive and flourish are going to change their business model from production to aggregating the networks and the network services and solutions. If you're a construction company or an IT company or a logistics company or an information data operation, to the extent that you can find ways to help build the commons, you can get some commercial value in that.

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.

Consumers deserve to know exactly what they're getting for their money when they sign-up for a 4G data plan.

Context is to data what water is to a dolphin

Customers need to be given control of their own data-not being tied into a certain manufacturer so that when there are problems they are always obliged to go back to them.

Data about an innovative idea is rarely crystal clear.

Data are just summaries of thousands of stories - tell a few of those stories to help make the data meaningful.

Data don't generate theory - only researchers do that.

Data-driven predictions can succeed-and they can fail. It is when we deny our role in the process that the odds of failure rise. Before we demand more of our data, we need to demand more of ourselves.