Data Mining Techniques and Business Intelligence

Data mining is almost a new term that refers to the procedure by which the comparative information is drawn out from huge data by examining relationships, using various tools like clustering, classification and many more. Today, there are several data mining techniques that are developed and executed, and this article helps you to know more about data mining techniques with tools.  

Data Mining Techniques:

Clustering:

It refers to the arrangement of data clusters that are organized together by similar relationship with them.  In other words, it is the relationship between dependent and independent variables that can be used to gain profit in the future.  

Classification:

Classification is one of the most used data mining technique. Depends on machine learning, it is used to arrange each item the on data set into one of the predefined groups. Mathematical techniques like statistics, linear programming and more are used for this type. For example, you can use this technique in the application which is based on the past record of a person who left the company.

Association:

Association, sometimes inaccurately referred as association rule learning. It is one of the most popular data mining techniques and it is used to determine the relationship of the specific item on other items within the same transaction. For Example, it is used to find out what products or services are used by the customers and it is particularly applied in market basket analysis.

Remember, we should use high quality data in all these data mining techniques to achieve a desired result.

Business Intelligence and Data Mining:

Gathering, storing and analyzing of data for the purpose of making business decisions, market and industry analysis are referred as business intelligence (BI). The Business intelligence is normally divided into data, analytics and business layers. Unlike the classic data mining technique, business intelligence is the advanced technique in data mining….

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