Soren Skou Quotes

The great temptation of Big Data is that we can stop worrying about comprehension and focus on preventive action instead. Instead of wasting precious public resources on understanding the 'why' - i.e., exploring the reasons as to why terrorists become terrorists - one can focus on predicting the 'when' so that a timely intervention could be made.

Strapped by tight credit and plummeting sales, businesses have overhauled the way they manage supply chains, inventory, production practices and staffing.

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.

Perhaps one day earthquakes, hurricanes and financial crashes will all be predictable. But we don't have to wait until then for seismology, meteorology and economics to become sciences; they already are.

Supply chains cannot tolerate even 24 hours of disruption. So if you lose your place in the supply chain because of wild behavior you could lose a lot. It would be like pouring cement down one of your oil wells.

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 world is now awash in data and we can see consumers in a lot clearer ways.

With this emergence of big data and social mobility, you will, in fact, see the death of 'average,' Instead, you will see the era of you.

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

Data scientist is just a sexed up word for statistician.

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.

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

Rethinking product supply chains offers another opportunity for traditional enterprises to introduce a host of positive outcomes.

'Data scientist,' as a profession, is largely a fad.

Artificial intelligence, machine learning... cell therapy, immunotherapy. There's just a constant stream of investment ideas we could pursue better in that fashion.

The big mystery of Big Data is causation versus correlation.

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.

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.

Amateurs do tactics, experts do logistics, as we learn in the military.

I love sophisticated algorithms that help consumers in a tangible way.

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

Whether baseball or football, we're tasked in front offices with making decisions under uncertainty. How do you corral that uncertainty in a way to make more consistently better decisions? That's very similar.

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.