Data mining is the process of discovering patterns in large data sets involving methods at the intersection of artificial intelligence, machine learning, statistics, and database systems. In other words, data mining is mining knowledge from data. It uses sophisticated mathematical algorithms to segment the data and evaluate the probability of future events.
While large-scale information technology has been evolving separate
transaction and analytical systems, data mining provides the link
between the two. Data mining software is one of a number of analytical tools for
analyzing data. It allows users to analyze data from many different
dimensions or angles, categorize it, and summarize the relationships
identified. It also able to answer questions that cannot be addressed through simple query and reporting techniques. Generally, any of four types of relationships are sought:
- Classes - Stored data is used to locate data in predetermined groups.
- Clusters - Data items are grouped according to logical relationships or consumer preferences.
- Sequential patterns - Data is mined to anticipate behavior patterns and trends.
- Associations: Data can be mined to identify associations. The beer-diaper example is an example of associative mining.
Data mining tools and techniques
Data mining techniques are used in many research areas, including mathematics, cybernetics, genetics and marketing. While data mining techniques are a means to drive efficiencies and predict customer behavior, if used correctly, a business can set itself apart from its competition through the use of predictive analysis.
Web mining - a type of data mining used in customer relationship management,
integrates information gathered by traditional data mining methods and
techniques over the web. Web mining aims to understand customer behavior
and to evaluate how effective a particular website is.
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