Data mining is all about data, i.e. extracting valuable information from the raw data. Data mining is the procedure of analyzing data from different dimensions and then summarizing it into useful information.  Data mining or knowledge discovery is often used in large organization to get meaning full information from the huge raw data collected from its different information systems. Data mining is expected to be “one of the most revolutionary developments of the next decade,” according to the online technology magazine ZDNET News. In fact, the MIT Technology Review chose data mining as one of ten emerging technologies that will change the world.

According to the Gartner Group, “Data mining is the process of discovering meaningful new correlations, patterns and trends by sifting through large amounts of data stored in repositories, using pattern recognition technologies as well as statistical and mathematical techniques.”

“Data mining is the analysis of (often large) observational data sets to find unsuspected relationships and to summarize the data in novel ways that are both understandable and useful to the data owner” (Hand et al. [5]).

“Data mining is an interdisciplinary field bringing togther techniques from machine learning, pattern recognition, statistics, databases, and visualization to address the issue of information extraction from large data bases” (Evangelos Simoudis in Cabena et al. [6]).

Use of Data mining

Data mining is used for variety of purposes such as

• Description
• Estimation
• Prediction
• Classification
• Clustering
• Association

We will discuss all of these terms in my next post.

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