Michael Lewis Quotes

Take the situation of a scientist solving a problem, where he has certain data, which call for certain responses. Some of this set of data call for his applying such and such a law, while others call for another law.

There's something that happens with the collection of a large amount of data when it's dumped into an Excel spreadsheet or put into a pie chart. You run the risk of completely missing what it's about.

Go out and collect data and, instead of having the answer, just look at the data and see if the data tells you anything. When we're allowed to do this with companies, it's almost magical.

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

Our problems are not with the data, itself, but arise from our interpretation of the data.

Big data is indeed a buzzword but it is one that is frankly under-hyped.

The goal is to turn data into information, and information into insight.

Personally, I find visualisations great for helping me understand the world and for sifting the huge amounts of information that deluge me every day.

All of the studies we do in my group are quantified.

Many people make the mistake of confusing information with knowledge. They are not the same thing. Knowledge involves the interpretation of information. Knowledge involves listening.

There is a tendency to mistake data for wisdom…

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

We mistake being able to get lots of information from everywhere very quickly with actually getting knowledge.

Analytics is not about sitting behind a computer and pushing enter and having it produce an answer.

The job of the data scientist is to ask the right questions.

It is difficult finding intelligence that is actionable in a lot of these places, but we have to keep trying.

Scientific data are not taken for museum purposes; they are taken as a basis for doing something. If nothing is to be done with the data, then there is no use in collecting any. The ultimate purpose of taking data is to provide a basis for action or a recommendation for action. The step intermediate between the collection of data and the action is prediction.

Teach where data can be found or how it can be derived, not the recording of data.

The analysis of data will not by itself produce new ideas.

Data really powers everything that we do.

What intrigues us as a problem, and what will satisfy us as a solution, will depend upon the line we draw between what is already clear and what needs to be clarified.

A desperation to escape a problem is the wrong way. A passion to understand it is the right way

Still, it is an error to argue in front of your data. You find yourself insensibly twisting them round to fit your theories.

The intellectual equipment needed for the job of the future is an ability to define problems, quickly assimilate relevant data, conceptualize and reorganize the information, make deductive and inductive leaps with it, ask hard questions about it, discuss findings with colleagues, work collaboratively to find solutions and then convince others.

Data are becoming the new raw material of business.