Technology is giving companies superpowers to compete more intelligently and capture the data behind changing trends, expanding markets, and new opportunities.
The core advantage of data is that it tells you something about the world that you didn't know before.
Even smaller companies are putting resources behind their analytics teams in the same way they put resources behind engineering and product teams. There are some great tools out there that allow even tiny businesses to use data effectively.
I decided that since I was trying to teach 'style' of thinking in science and engineering, and 'style' is an art, I should therefore copy the methods of teaching used for the other arts - once the fundamentals have been learned.
Data science is the combination of analytics and the development of new algorithms.
You really need to have a lot of empathy for the work you're doing and the people who you're ultimately trying to help, whether that's a business colleague, a boss, or, ultimately, the user of the software you're building.
I joined bit.ly as chief scientist in October of 2009. The company is a URL-shortener and content-sharing platform; we provide tools for people to share and track links on the Internet.
If you find something obscure fascinating, learn as much about it as you can, because there's a good chance it won't be obscure for long.
The job of the data scientist is to ask the right questions.
The sender and subject line are actually the most important parts of an e-mail because people tend to put more important information in the subject.
In tech entrepreneurship, even a lot of hack events tend to be overly commercial in that they're designed to produce companies.