Hilary Mason Quotes

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.

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.

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.

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.

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.

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.

I learned analytics. It's a point of reference, of information. It has to be a factor in decision making.

The big mystery of Big Data is causation versus correlation.

I'm an analytics girl.

In disciplines as disparate as baseball, financial services, trucking and retail, people are realizing the power of data to help make better decisions.

Data drives success. That is how we began our success with eSpeed. It was always based on the data.

I keep saying the sexy job in the next ten years will be statisticians. People think I'm joking, but who would've guessed that computer engineers would've been the sexy job of the 1990s?

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.

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.

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

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.

When human judgment and big data intersect there are some funny things that happen.

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

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'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.

The premise and promise of Big Data is that there are no stories, only patterns; that the human preference for story is aligned with the human tendency for error; and that only through dislocations in scale - the scale of sample size and of time - will truth emerge.

I think of 'data science' as a flag that was planted at the intersection of several different disciplines that have not always existed in the same place. Statistics, computer science, domain expertise, and what I usually call 'hacking,' though I don't mean the 'evil' kind of hacking.

I like to say I've been working on big data for so long, it used to be small data when I started working on it.

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