Gurjeet Singh Quotes

The possibilities for creation and insight are endless. We're constantly collecting more data, and it's starting to be very relevant to our lives.

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

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.

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

Networks love data. They love to be able to look at numbers and try to predict what they think will 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.

Personally, I find visualisations great for helping me understand the world and for sifting the huge amounts of information that deluge me every day.

Big data has been used by human beings for a long time - just in bricks-and-mortar applications. Insurance and standardized tests are both examples of big data from before the Internet.

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.

We're rapidly entering a world where everything can be monitored and measured. But the big problem is going to be the ability of humans to use, analyze and make sense of the data.

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.

We are going to completely change what it means to do advanced analytics with our data solutions. We have machine-learning stuff that is about really bringing advanced analytics and statistical machine learning into data-science departments everywhere.

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

Data is a tool for enhancing intuition.

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.

Data science is the combination of analytics and the development of new algorithms.

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

Computers ought to help people find their own best path through lots of textual information.

There's definitely a huge opportunity for businesses to transform their operations and decision making by using data.

The purpose of computing is insight, not numbers.

One of the things we did at PayPal was collaborative filtering and machine learning: looking at patterns of human behavior. We used it there to predict when people would try to cheat the system to get money. But you can predict pretty much any behavior with a certain amount of accuracy.