Data Mining

Data Mining is the process of discovering patterns in large data. The patterns discovered must be meaningful in that they lead to some advantage [14]. It is about solving problems presenting in databases. It uses artificial intelligence techniques, neural networks, and advanced statistical tools such as cluster analysis that reveal trends, patterns, and relationships, which might otherwise have remained undetected. In contrast to an expert system which draws inferences from the given data on the basis of a given set of rules data mining attempts to discover hidden rules underlying the data.

Data mining involves learning which ties to performance rather than knowledge. On the other hand, Machine learning is ideal for exploiting the hidden opportunities in big data and extracting value from big and disparate data sources and suited for complexity of dealing with these data [91]. Machine learning is a type of artificial intelligence (AI) that allows software applications to become more accurate in predicting outcomes without being explicitly programmed.

The processes involved in machine learning are similar to data mining. Both require searching through data to look for patterns and adjusting program actions accordingly. Data mining has been used by a wide range of applications such as business, medicine, science, and engineering. It has led to numerous beneficial services to many walks of real business.

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