Paul DePodesta Quotes

The purpose of computing is insight, not numbers.

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.

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.

I'm an analytics girl.

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.

While data can only tell you what has happened in the past, it can in some ways give you a sense of what might be of interest to an audience in the future.

There are a number of fascinating stories included in 'The Human Face of Big Data' that represent some of the most innovative applications of data that are shaping our future.

Every part of your business will change based on what I consider predictive analytics of the future.

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

The people who are thinking most about big data right now are corporations and governments.

Graphics has lately made a great shift towards machine learning, which itself is about understanding data.

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

When you have mastered numbers, you will in fact no longer be reading numbers, any more than you read words when reading books You will be reading meanings.

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.

People are saying, 'Big Data is the new oil.'

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.

If you have a lot of data and you want to create value from that data, one of the things you might consider is building up an AI team.

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.

Everyone talks about how much data's in the world. Except, actually, 80% of it is pretty blind to computers. I mean, it can store it. But if it's a movie, a poem, a song, it doesn't know what it's actually saying or doing.

The big mystery of Big Data is causation versus correlation.

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

We know now data is so powerful, and you can learn so much about yourself and creating product with data.

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