For data analysts like myself, one of the most useful pages on any blog resides on this website. The comprehensive list of data sites Andreas put together is indispensable because finding numerical data online, even though it is abundant, is so difficult and time consuming.
Any real world data user knows the pain of Googling for numerical data. Many times I have spent tens of minutes and sometimes hours trying to find data on the web. If I eventually find data, and often I do, I then spend time validating, formatting and cleaning the data.
I think this is a universal experience: Any real-world data analyst knows, the blood, sweat and tears are not in the analysis of data, they’re in the acquisition of data.
One day, several years ago, after another long battle trying to find data, I realized that I, (and no doubt many others), needed someone to create the “Wikipedia of Numerical Data”. At that moment, I became acutely aware of the difference between quantitative knowledge on the internet and qualitative knowledge. The latter is beautifully and comprehensively organized by Wikipedia. On the other hand, quantitative knowledge, (numerical data), is scattered across thousands of different web sites in hundreds of different formats and is generally difficult to find and difficult to use.
So I am now on a mission to build “Wikipedia for Numerical Data”. I am doing this not by asking publishers to put their data on my site, but rather by building a smart index that knows where to get data when a user wants it. My site, www.quandl.com, is something akin to a search engine for numerical data.
Quandl is open and free. It is curated and maintained by a (thus far) small team of like minded individuals. My goal is to recruit more help and make it so that there is a one easy to use site where you can get any numerical data you need.
If you are interested in learning more about our objectives or perhaps even getting involved, please visit our site where you will find my email address with little difficulty.