The increasing size of the available data and database volumes represents a real challenge for the data management community. In general, current approaches in data mining require the data to be first extracted from an underlying database. From a practical point of view, this presents many drawbacks. In this short article, we present a possible solution to bridge the gap between data repositories and end user analysis. We demonstrate the interestingness of this approach with ibmdbpy, an open source Python interface developed by IBM for database administration and data analytics.