It's amazing how much data is out there. The question is how do we put it in a form that's usable?
Data is not useful until it becomes information.
There's a lot of power in executing data - generating data and executing data.
We all have so much access to the information on the Internet and in books, but we don't necessarily get that information in a usable way so that we can turn information into action.
A computer is a machine for constructing mappings from input to output.
You can't put rubbish into a computer and get something good out.
Every decoding is another encoding.
You and I are streaming data engines.
Every time a bit of information is erased, we know it doesn't disappear. It goes out into the environment. It may be horribly scrambled and confused, but it never really gets lost. It's just converted into a different form.
I think of myself as a translator. I just change the dry, unfeeling language of data into a visual language that allows for feeling.
Data, I think, is one of the most powerful mechanisms for telling stories. I take a huge pile of data and I try to get it to tell stories.
It can always be transformed into an avenue of information.
Every physical system registers information, and just by evolving in time, by doing its thing, it changes that information, transforms that information, or, if you like, processes that information.
If you have information you've got the world by the balls. But we have to convert information into knowledge in order to make it humanly useful.
Amazing things happen when you pull individual pieces of information together into larger linked datasets: meaning emerges, as you produce facts from figures.
My particular interest for the past couple of years has been to really think deeply about the big impendence mismatch we have between programming languages, C# in particular, and the database world, like SQL or, for that matter, the XML world, like XQuery and those languages that exist.
Data is just like crude. It’s valuable, but if unrefined it cannot really be used. It has to be changed into gas, plastic, chemicals, etc to create a valuable entity that drives profitable activity; so must data be broken down, analyzed for it to have value.
My job is to analyze our data set to understand it and build products on it. I look at raw data, do the math to clean it up, and build systems to make it easy to understand.
