Data mining is the process of analyzing large amounts of data in order to find patterns and commonalities.
Data mining, also known as knowledge discovery, is the process of digging through and analyzing enormous sets of data and then extracting the meaning of the data. Data mining tools like SQL Server Analysis Services, predict behaviors and future trends, allowing businesses to make proactive, knowledge-driven decisions. Data mining tools can answer business questions that traditionally were too time consuming to resolve. They scour databases for hidden patterns, finding predictive information that experts may miss because it lies outside their expectations. Input to learning mining algorithms is called cases, samples, examples, instances, events, and observations.
- machine-learning, artificial-intelligence and statistics provide many techniques used in data mining, in combination with database technologies for efficiency. Please use the appropriate tag (e.g. machine-learning) to refer to the raw methods.
Cluster analysis (dataclustering) and outlier detection (outliers) are two of the main challenges from data mining.
- Data Mining Introduction
