Chamath Palihapitiya 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.

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

Every part of your business will change based on what I consider predictive analytics of the future.

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

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

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.

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.

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.

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.

My mission is to bring the power of big data insights and analytics to every company.

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.

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

The people who are thinking most about big data right now are corporations and governments.

Business analytics or predictive modelling is a $100 billion industry, and $41 billion is spent on outsourced business analytics every year. I think that's about twice the size of the movie industry - it's really big.

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.'

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.

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

When I look at the next set of technologies that we have to build in Salesforce, it's all data-science-based technology. We don't need more cloud. We don't need more mobile. We don't need more social. We need more data science.

The answers to today's most important scientific, business, and social problems lie in data.

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

Technologies like Ayasdi's exist now to automatically discover information from data without having someone making guesses up front.

The big mystery of Big Data is causation versus correlation.