Gurjeet Singh Quotes

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.

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 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.

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.

Big Data is just that - big. But, it's a term that is largely misunderstood and difficult to explain.

I love data. I think it's very important to get it right, and I think it's good to question it.

Most of 'big data' is a fraud because it is really 'dumb data.'

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.

I think you can have a ridiculously enormous and complex data set, but if you have the right tools and methodology then it's not a problem.

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.

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'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.

I'm very lucky to work at bitly, with a data set that allows us to explore human social behavior at the scale of human social behavior.

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

The big mystery of Big Data is causation versus correlation.

A lot of people seem to think that data science is just a process of adding up a bunch of data and looking at the results, but that's actually not at all what the process is.

You need to use data science and machine learning to get the ground truth of what's happening inside of a company.

For me, the most exciting aspect of my success is how the insights that Ayasdi's technology has found in data can truly impact people's lives.

The next darwin is more likely to be a data wonk than a naturalist wandering through an exotic landscape.

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