Data mining is an intelligent application of data warehousing. It is a process of selecting business-relevant information from a very large data set. "It is a process of discovering significant new relationships, patterns and trends by analyzing large data sets using pattern recognition and statistical and mathematical techniques" (Eric Brethenoux, Gartner Group).
Data mining is a data filtering process in which stored data is examined for topic-specific relationships and regularities. Through data extraction, filtering and aggregation of the stored data, hidden patterns and relationships between the data can be uncovered and converted into insights relevant to production, sales or marketing. In addition, data mining can be used to derive conclusions about future trends. The data extracted by data mining can only be recognized by the links that are determined by means of path analyses.
Data mining distinguishes between two basic methods: validating on the data and developing hypotheses from the data.
Data mining can be used to identify certain inferences and relationships from the data in a data warehouse. For example, a correlation of the frequency of vacations for a certain segment of the population could be identified, or the purchasing behavior for certain products in relation to a certain clientele. The classification and analysis of large data sets is referred to as Big Data Analytics.