When analyzing data, actual analysis usually isn't your only task -- in fact, sometimes it's not even the most daunting. Acquiring, formatting and removing errors from data can pose significant challenges (not to mention take up lots of time).

"I have probably spent weeks of my life trying to find data on the web," founder Tammer Kamel writes in a blog post at Revolution Analytics. "And several more weeks validating, formatting and cleaning the data. "

"We've built a sort of 'universal data parser' which has thus far parsed about 2.8 million datasets," Kamel explained in his post. That's created a "sort of search engine for numerical data. The idea with Quandl is that you can find data fast. And more importantly, once you find it, it is ready to use. This is because Quandl's bot returns data in a totally standard format. Which means we can then translate to any format a user wants."

Quandl started by providing data in Excel, CSV, XML and JSON formats. They've got a beta add-in for Excel that allows you to pull one of their data sets directly into your spreadsheet (free API token needed) and just launched a package for R, the open-source R Project for Statistical Analysis platform. "Python, Ruby, Matlab, and Stata are next," Kamel told ProgrammableWeb.com. They also have an API so you can pull the data into your own applications -- there's even an "API call" option with every data