Each time you withdraw money from a bank, make a phone call, log onto the Internet, rent a video, or even claim flybuy points at a supermarket, the transactions are more often than not recorded and stored by computers. As a result, masses and masses of data megabytes , gigabytes , terabytes are piling up in the electronic vaults of companies, governments and research institutions. Up until the early 1990s, the answer to this was not much . But statisticians and data miners now have faster analysis tools that can help sift and analyse the stockpiles of data, turning up valuable and often surprising information. Data mining can be defined as the exploration and analysis of large data sets, in order to discover meaningful patterns and rules.
Automation is essential.
Staring at a huge spreadsheet is not a good way to analyse any data. The trick is to find effective ways to combine the computer's power to process data with the human eye's ability to detect patterns. The techniques of data mining are designed for, and work best with, large data sets. How data mining works Data mining is a component of a wider process called knowledge discovery from databases . It involves scientists from a wide range of disciplines, including mathematicians, computer scientists and statisticians, as well as those working in fields such as machine learning, artificial intelligence, information retrieval and pattern recognition.