Matt Mullenweg Quotes

Digg will serve as a means of gathering metrics for third party websites, providing them insights into who's digging their content, who they are spreading it to.

If you need help identifying actionable analytics check out this post.

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.

Big data is mostly about taking numbers and using those numbers to make predictions about the future. The bigger the data set you have, the more accurate the predictions about the future will be.

People used to pooh-pooh the idea of a check-in, saying that this wasn't interesting. But when you have 3 billion of those data points, you can take any latitude and longitude anywhere in the world, and I'll tell you what is interesting now, 20 minutes from now, and 6 hours from now.

At any time of day, hundreds of different versions of Facebook are running on the Internet - with a changed color here, a moved button there - and the user response to each variation is measured. And the same is done with advertising.

You take the noise and put it in data information knowledge, and you get insight from that knowledge. How to execute the trade, the timing, sizing, long, short, and then you risk manage it.

Evolving technologies that allow economists to gather new types of data and to manipulate millions of data points are just one factor among several that are likely to transform the field in coming years.

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.

Social media has given companies access to unprecedented amounts of information on client behavior and preferences - so-called Big Data. But making sense of it all and turning it into actionable policy has been elusive.

The Government are very keen on amassing statistics - they collect them, add them, raise them to the nth power, take the cube root and prepare wonderful diagrams.

On average, people should be more skeptical when they see numbers. They should be more willing to play around with the data themselves.

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.

Rob Engle and I are concerned with extracting useful implications from economic data, and so the properties of the data are of particular importance.

The people at Netflix are extremely intelligent about the way they monitor activity on their platform.

There's a blizzard of metrics that social sites and messaging sites put out there.

I'm really curious about people - what their desires and interests are - and bit.ly's data tell me that. It gives me an unprecedented window into human communication and behavior.

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.

Every day we have teams looking for new data sets.

My mission is to bring the power of big data insights and analytics to every company.

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

If we just focus on stats, we're gonna eventually not have them.

It's a huge competitive advantage to see in real time what's happening with your data.

There's been the emergence of a philosophy that big data is all you need. We would suggest that, actually, numbers don't speak for themselves.