Knowledge Acquisition in Databases

Knowledge discovery and acquisition in databases features as a separate discipline of business intelligence. Generally speaking, it denotes the process of analysing large quantities of data, its goal being to discover new information and knowledge, and apply them in resolving business problems. More specifically, it implies to data acquisition - or mining - as the initial step, using data-driven learning algorithms, and is aimed at establishing their mutual correlations. Due to its popularisation, significantly supported by computing technology development, the notion of data mining has gradually come to be equated with knowledge discovery. This article deals with knowledge acquisition from databases, i.e. data mining with OLAP (On-Line Analytical Processing) tools, which enable multidimensional data management and graphic presentation thereof. Such an approach is mostly applicable when analysing smaller data sets, i.e. in the phase of data preparation for mining, in order to better understand or select variables included in the business information process.