In this podcast I discuss the (sometimes) wrong use of the term Data Mining, with in accord to the paper From Data Mining to Knowledge Discovery in Databases, written in 1996 by Usama Fayyad, Gregory Shapiro, and Padhraic Smyth,  is defined as: Data mining is a step in the KDD process that consists of applying data analysis and discovery algorithms that produce a particular enumeration of patterns (or models) over the data. KDD means Knowledge Discovery in Databases, and is composed by the following steps: Data -> (selection) -> Target Data -> (preprocessing) -> Preprocessed Data -> (transformation) -> Transformed Data -> (data mining) -> Patterns -> (interpretation/evaluation) -> Knowledge Several authors call Data Mining when they are performing the entire cycle (from Data to Knowledge) and not only the data mining step, which can be represented also by the use of classification/clustering algorithms. The reference paper is available at: https://wvvw.aaai.org/ojs/index.php/aimagazine/article/download/1230/1131 Follow my podcast: http://anchor.fm/tkorting Subscribe to my YouTube channel: http://youtube.com/tkorting The intro and the final sounds were recorded at my home, using an old clock that belonged to my grandmother. Thanks for listening