Most financial analysis is based on historical data so understanding where to get it and what to do with it is important. For many years data was either not available or it was locked away behind online pay-walls. Luckily for us we are in the midst of an open source data movement. Open market data is market data which is freely available to everyone to use and republish as they wish, without restrictions from copyright, patents or other mechanisms of control. This page highlights some of the best sources of open source data which can be used for algorithmic trading, quantitative finance, and machine learning. If you know of any more sources, please mention them in the comments below.

In addition to these two sources the following sources also provide a lot of meaningful market data: Amazon Web Services Data provides data which can be seamlessly integrated into AWS cloud-based applications; The World Bank provides free and open access to data about development in countries around the globe; Google Finance offers similar information to Yahoo Finance and has some cool features for portfolios; the UCI machine learning data provides useful data sets for testing machine learning algorithms on different types of problems; MLData also provides open source machine learning data sets for testing different algorithms, and DataBib offers a searchable directory of research open source data repositories. That said, many of these data-sets are aggregated on Quandl.com for convenience.