Data Mining

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Definition: Data Mining

Data mining is defined as the extraction of hidden tacit information from large databases and is a powerful new technology with high potential to help companies focus on implicit information hidden in their large data warehouse. The database is searched for hidden patterns, giving the information which otherwise would have been hard to notice or which was beyond expectations. Data mining is especially useful to predict future trends and behaviors of the consumers. Knowing about the future trends in advance makes it possible for a company to take proactive decisions.

In contrast to retrospective tools which offer information about the past events, a tool like data mining offers a prospective analysis of what may happen in near or coming future. Data mining can give a company the information which earlier was either impossible to get or was too time or money consuming.

Many companies have already been utilizing this powerful tool since long, and others have now realized its potential to decipher customer behavior, product placement, upcoming trends, etc. Data mining techniques can be implemented easily on existing software and hardware platforms and can be integrated with new system, as and when required.

Data mining involves six common classes of tasks, namely - anomaly detection, Association rule learning, Clustering, Classification, Regression, Summarization, and Sequential pattern mining. Any one of them, but usually a combination of these is used on a database to make something out of it.

There are different levels of analysis available in data miming. Some of the widely used ones are:

  • Artificial neural networks
  • Genetic algorithms
  • Decision trees
  • Nearest neighbor method
  • Rule induction
  • Data visualization

Hence, this concludes the definition of Data Mining along with its overview.

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