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What Is Data Mining?

In: Computers and Technology

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What Is Data Mining?
Data mining is the practice of automatically searching large stores of data to discover patterns and trends that go beyond simple analysis. Data mining uses sophisticated mathematical algorithms to segment the data and evaluate the probability of future events. Data mining is also known as Knowledge Discovery in Data (KDD).
The key properties of data mining are: * Automatic discovery of patterns * Prediction of likely outcomes * Creation of actionable information * Focus on large data sets and databases
Data mining can answer questions that cannot be addressed through simple query and reporting techniques.
Automatic Discovery
Data mining is accomplished by building models. A model uses an algorithm to act on a set of data. The notion of automatic discovery refers to the execution of data mining models.
Data mining models can be used to mine the data on which they are built, but most types of models are generalizable to new data. The process of applying a model to new data is known as scoring.
See Also:
Oracle Data Mining Application Developer's Guide for a discussion of scoring and deployment in Oracle Data Mining
Prediction
Many forms of data mining are predictive. For example, a model might predict income based on education and other demographic factors. Predictions have an associated probability (How likely is this prediction to be true?). Prediction probabilities are also known as confidence (How confident can I be of this prediction?).
Some forms of predictive data mining generate rules, which are conditions that imply a given outcome. For example, a rule might specify that a person who has a bachelor's degree and lives in a certain neighborhood is likely to have an income greater than the regional average. Rules have an associated support (What percentage of the population satisfies the rule?).
Grouping
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