Streamlining a meteorological database for knowledge discovery

Knowledge discovery in databases (KDD) is a multi stage process for extracting non trivial information from databases; two such stages are data preparation and data mining. We show how KDD techniques have been applied to a meteorological database to search for climatic patterns between geographical locations and how the size and quality of the data give rise to problems in the data mining stage