A Quote by Thomas Carlyle

There is so much data available to us, but most data won't help us succeed. — © Thomas Carlyle
There is so much data available to us, but most data won't help us succeed.
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.
Radio astronomy reflects our fascination with how audio can be used to understand information or ideas. Just as scientists visualize data through charts and pictures, we can use 'data sonification' to translate radio signals into sound that help us better understand some of our most enigmatic planetary systems.
I'm worried about privacy - the companies out there gathering data on us, the stuff we do on Twitter, the publicly scrapeable stuff on Facebook. It's amazing how much data there is out there on us. I'm worried that it can be abused and will be abused.
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.
Librarians are more important than ever before ... are uniquely qualified to help all of us separate the digital wheat from the chaff, to help us understand the reliability of the data we encounter.
We need a new generation of executives who understand how to manage and lead through data. And we also need a new generation of employees who are able to help us organize and structure our businesses around that data.
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.
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.
As we become so visible in the digital world and leave an endless trail of data behind us, exactly who has our data and what they do with it becomes increasingly important.
The information highway is being sold to us as delivering information, but what it's really delivering is data... Unlike data, information has utility, timeliness, accuracy, a pedigree... Editors serve as barometers of quality, and most of an editor's time is spent saying no.
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.
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.
The weaker the data available upon which to base one's conclusion, the greater the precision which should be quoted in order to give the data authenticity.
There's a project that I started at HHS called the Health Data Initiative. The whole idea was to take a page from what the government had done to make weather data and GPS available back in the day.
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.
This site uses cookies to ensure you get the best experience. More info...
Got it!