Will Self Quotes

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.

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 Government are very keen on amassing statistics - they collect them, add them, raise them to the nth power, take the cube root and prepare wonderful diagrams.

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.

It is easy to lie with statistics. It is hard to tell the truth without it.

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.

Numbers can't speak for themselves, and data sets - no matter their scale - are still objects of human design.

Data drives success. That is how we began our success with eSpeed. It was always based on the data.

Algorithms don't do a good job of detecting their own flaws.

There is a reasonable concern that posting raw data can be misleading for those who are not trained in its use and who do not have the broader perspective within which to place a particular piece of data that is raw.

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.

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

Like dreams, statistics are a form of wish fulfillment.

Forget artificial intelligence - in the brave new world of big data, it's artificial idiocy we should be looking out for.

The Government are very keen on amassing statistics; they collect them, add them, raise them to the nth power, take the cube root and prepare wonderful diagrams. But what you must never forget is that every one of those figures comes in the first instance from the village watchman, who just puts down what he damn pleases.

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 numbers are hard to control.

The bigger a data set that you have, the more polls, the more surveys that you have that people undertake, the more accurate your models are going to be. That's just a fact of data science.

The big mystery of Big Data is causation versus correlation.

If we just focus on stats, we're gonna eventually not have them.

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

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

To learn something from your data, the forming of a hypothesis lies with the human being, which turns into a query, which becomes a result. The problem is that there are too many queries to make, too many questions to ask.

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