David McCandless Quotes

Here's the thing: If you're monitoring every single thing that goes on in a given culture, if you have all the information that is there to be had, then that is the equivalent of having none of it. How are you going to process that amount of information?

To learn something from your data, the forming of a hypothesis lies with the human being, which turns into a query, which becomes a result. The problem is that there are too many queries to make, too many questions to ask.

There's something that happens with the collection of a large amount of data when it's dumped into an Excel spreadsheet or put into a pie chart. You run the risk of completely missing what it's about.

Faced with information overload, we have no alternative but pattern-recognition.

Data, I think, is one of the most powerful mechanisms for telling stories. I take a huge pile of data and I try to get it to tell stories.

The problem with data is that it says a lot, but it also says nothing. 'Big data' is terrific, but it's usually thin. To understand why something is happening, we have to engage in both forensics and guess work.

Information is expanding daily. How to get it out visually is important.

Collecting intelligence information is like trying to drink water out of a fire hydrant. You know, in hindsight It's great. The problem is there's a million dots at the time.

We're not in an information age anymore. We're in the information management age.

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.

We have entered an era where the kinds of data and analyses that people run have gotten incredibly complicated. So you have researchers using sophisticated software programs that they probably don't understand but are generally accepted and everyone [in the field] uses.

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 job of the data scientist is to ask the right questions.

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.

The power of Ayasdi is its unique ability to automatically discover insights - regardless of complexity - without asking questions.

Ayasdi's customers can finally learn the answers to questions that they didn't know to ask in the first place.

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.

When the world throws you too much information, the only way you can stay sane or survive is to look for pattern recognition. Amidst all the blurs, is there a constellation that emerges, is there a straight line that's emerging. I think as long as you keep your mind in the palce where you're actively looking for patterns, you may not be safe, but you're going to feel safe, I think.

Big data is indeed a buzzword but it is one that is frankly under-hyped.

We're flooding people with information. We need to feed it through a processor. A human must turn information into intelligence or knowledge.

The impulse to collect data preceded the ability to make sense of it. People facing a complicated problem measure whatever they can easily measure. But the measurements by themselves don’t lead to understanding.

The problem with Google is you have 360 degrees of omnidirectional information on a linear basis, but the algorithms for irony and ambiguity are not there. And those are the algorithms of wisdom.

Computers can't find the unexpected, but people can when they eyeball the data.

Every day we have teams looking for new data sets.

Technologies like Ayasdi's exist now to automatically discover information from data without having someone making guesses up front.