Sam Yagan Quotes

One experiments and has to choose always the best results.

My background is putting in large systems that change lives... The right kind of systems can bring honesty and efficiency.

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

I'm not being evasive but I am saying I'm not a scientist and I'm not directly involved in the consultation however the science must be sound, it must be agreed and the consultation must be of a high quality or no one will have any confidence in the process.

I love data. I think it's very important to get it right, and I think it's good to question it.

One of the things that's making ArcGIS come alive is apps. Apps are opening up the ArcGIS platform, making it available to everybody in your organization as well as to the public.

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

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

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.

Sharing data allows us to research, communicate, consume media, buy and sell, play games, and more. In return, businesses develop products, scientists undertake research, and governments use data to enable voting, inform policies, collect tax, and provide better public services.

If the data do not prove that indexing wins, well, the data are wrong.

Bosses and leaders everywhere should cherish the people who bring them bad news, disappointing data or hard problems.

Above all else show the data.

Data is the new soil, because for me, it feels like a fertile, creative medium. Over the years, online, we've laid down a huge amount of information and data, and we irrigate it with networks and connectivity, and it's been worked and tilled by unpaid workers and governments.

The ultimate purpose of collecting the data is to provide a basis for action or a recommendation.

[Women] tend to collect more pieces of data when they think, put them into more complex patterns, see more options and outcomes. They tend to be contextual, holistic thinkers.

It's amazing how much data is out there. The question is how do we put it in a form that's usable?

Even more important than statistics is then having the staff that can take the data and ensure it's presented in a way that improves individuals and teams.

I think data is incredibly powerful for understanding what people are thinking and for allocating resources.

Data is not intelligence.

I'm a very good decision maker because I have core set of principles and so I can make decisions. Decisions can be very hard and you have to wrestle with them, but I'm able to get all the data on the table and figure out what would be the best decision because decisions mean ill for some people and mean positives for others.

You have to be willing to have the decision-making follow the data.

Early in a startup, product decisions should be hunch driven. Later on, product decisions should be data driven.

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

We do a lot of "capital I" important stories, but one I'd highlight is the work we've done on guns, not only for the acclaim it's gotten but also because it showcases all the different kinds formats we use. So we compiled a database of all the variables of all the mass shootings in America - work the government doesn't do, thanks to the NRA - which allowed us to surface patterns and make data visualizations of it.