Brittany Kaiser Quotes

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.

The big mystery of Big Data is causation versus correlation.

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

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.

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.

Every day we go over data and use science and data to drive policy and decision-making.

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.

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

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

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

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

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.

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.

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

The ability to collect, analyze, triangulate and visualize vast amounts of data in real time is something the human race has never had before. This new set of tools, often referred by the lofty term 'Big Data,' has begun to emerge as a new approach to addressing some of the biggest challenges facing our planet.

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

Good data is hard to find. Hard data is good to find.

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.

Every company has messy data, and even the best of AI companies are not fully satisfied with their data. If you have data, it is probably a good idea to get an AI team to have a look at it and give feedback. This can develop into a positive feedback loop for both the IT and AI teams in any company.