Satya Nadella 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.

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.

The big mystery of Big Data is causation versus correlation.

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.

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.

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.

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.

Our ability to do great things with data will make a real difference in every aspect of our lives.

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

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

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.

Deep learning allows you to create predictive models at a level of quality and sophistication that was previously out of reach. And so deep learning also enhances the product function of data science because it can generate new product opportunities.

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 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.

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.

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

The world is looking for big data scientists, and there just aren't enough to go around.

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

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

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.