Hilary Mason Quotes

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.

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'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.

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.

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.

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.

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.

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.

Machine learning is the science of getting computers to learn without being explicitly programmed.

The whole concept of data science is that the software becomes the expert, and you, as the average user, are able to understand what's going on.

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.

The big mystery of Big Data is causation versus correlation.

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

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.

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

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

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.

It's difficult to imagine the power that you're going to have when so many different sorts of data are available.