June 23, 2016
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Quandl Founder Tammer Kamel wants to create a new Wikipedia for Numeric Data. Quandl has built a sort of "universal data parser" which has thus far parsed about 2.8 million datasets without anything from any data publisher. As long as they spit out data somehow (excel, text file, blog post, xml, api, etc) the "Q-bot" can slurp it up. The result is quandl.com as sort of "search engine" for numerical data. Quandl's bot returns data in a totally standard format. The idea with Quandl is that you can find data fast, and it is ready to use.
The ability to analyze information and use the results to make more informed decisions is something that interests a lot of people. Developers, publishers, and small to large business owners all collect an overwhelming amount of data pertaining to the work that they do. Employing a staff of analysts to sift through the onslaught of what can sometimes seem to be useless information is obviously one way to solve this problem, ‘Machine Learning’ is another.