Data Mining and its Components
Data mining “means discovering new information from very large data sets” (Ricardo, 2012, p. 746), in other words is defined as searching, analyzing and sifting through large amounts of data to find relationships, patterns, or any significant statistical correlations. It is the process of extracting patterns from large data sets by combining methods from statistics and artificial intelligence with database management. It 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 mining have five major components:
• Extract, transform & load transactions data onto data warehouse system.
• Store & manage the data in a multi dimensional database system.
• Provide data access to business analysts & information technology professionals.
• Analyze the data by application software.
• Present the data in a useful format, such as table or graph.
Examples of earliest data mining used in retail supermarket, banking, financial markets etc, also is use in new applications for example Biological data mining, data mining in crime prevention or bio-informatics, pharmaceutical industry are the latest applications.
Although biological data mining can be considered under application exploration or mining complex types of data, the unique combination of complexity, richness, size, and importance of biological data warrants special attention in data mining. Data mining techniques are used for an automatic classification of newly discovered celestial bodies
Data mining technique is not perfectly...