To technically define the process of ‘data mining’, one could say that it is an automated extraction of information for their predictive analysis. This information is hidden into the overwhelming amounts of databases.
To put it in simple words, retrieval of data that is deemed to be important from the large amounts of datasets or data. This data is then presented in an analyzed form for the purpose of making decisions for the business.
The process of data mining requires putting into use the various types of mathematic algorithms as well as statistical techniques thrown in together along with software tools.
The use of BI Data mining is implemented for the purpose of market research, competitor analysis and for industry research.
What Are The Steps Involved In Data Mining?
Storage of Data: There is an enormous amount of data available around us, and more data is being generated every second. There is a need for storage of this data, and the pre-processing steps are quite essential for the success of its analysis.
Selection of responses: Selection of the response variable that are appropriate should be done and one should decide the figure of variables that should be examined.
Screening of the data: For outliers, there is a need for screening the data. Other missing values have to be addressed, these include values that are omitted or those appropriately imputed by one of the many methods available.
Determination and Analysis of the Data: There is a need for the data sets to be divided into evaluation and training data sets. In the case of data sets that are very large, they can’t be interpreted and analyzed so easily, therefore for doing so, the data should be sampled.