Data mining, also called data or knowledge discovery is the process of analyzing data from different perspectives and summarizing it into useful information - information that can be used to increase revenue, cuts costs, or both. 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. Technically, data mining is the process of finding correlations or patterns among dozens of fields in large relational databases.

Data
Data are any facts, numbers, or text that can be processed by a computer. Today, organizations are accumulating vast and growing amounts of data in different formats and different databases. This includes:

• Operational or transactional data such as, sales, cost, inventory, payroll, and accounting.

• Nonoperational data, such as industry sales, forecast data, and macro economic data.

• Meta data - data about the data itself, such as logical database design or data dictionary definitions.

Information
The patterns, associations, or relationships among all this data can provide information. For example, analysis of retail point of sale transaction data can yield information on which products are selling and when.

Knowledge
Information can be converted into knowledge about historical patterns and future trends. For example, summary information on retail supermarket sales can be analyzed in light of promotional efforts to provide knowledge of consumer buying behavior. Thus, a manufacturer or retailer could determine which items are most susceptible to promotional efforts.

Data mining is primarily used today by companies with a strong consumer focus. It enables these companies to determine relationships among "internal" factors such as price, product positioning, or staff skills, and "external" factors such as economic indicators, competition, and customer demographics. And, it enables them to determine the impact on sales, customer satisfaction, and corporate profits. Finally, it enables them to "drill down" into summary information to view detail transactional data.

While large-scale information technology has been evolving separate transaction and analytical systems, data mining provides the link between the two. Data mining software analyzes relationships and patterns in stored transaction data based on open-ended user queries. 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.

• Associations: Data can be mined to identify associations.

• Sequential patterns: Data is mined to anticipate behavior patterns and trends.

• Extract, transform, and load transaction data onto the data warehouse system.

• Store and manage the data in a multidimensional database system.

• Provide data access to business analysts and information technology professionals.

• Analyze the data by application software.

• Present the data in a useful format, such as a graph or table.