To technically define the process of’data mining’, one could say 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 examined form for the purpose of making decisions for the business. The process of data mining requires putting into use the various kinds of mathematical 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, competition analysis and for industry research. What are the steps involved in data mining? There is an enormous amount of data available around us, and more data is being generated every second. Are you hunting for web mining? Visit the before described site.
There’s a need for storage of this data, and the pre-processing measures are quite vital for the achievement of its analysis. Selection of responses. Choice of the response variable that are appropriate should be done and one should decide the figure of variables which should be examined. Screening of the data. For outliers, there is a need for screening the data. Other missing values need to be addressed, these include values that are omitted or people appropriately imputed by one of many methods available. Determination and analysis of the data. There’s a need for the data sets to be divided into training and evaluation 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 must be sampled. Visualization of the data. Before the application of sophisticated models, the data has to be summarized as well as visualized. By the use of basic graphs inclusive of line graphs and bar charts, scatter plots, plus matrix plots, histograms and box plots, an individual can use them for time series, categorizing the variables, display the correlation matrices, and multidimensional graphs with color, to overlay plots, visualization of the network data, Geo maps as well as spatial data, etc.
All of these are used for the purpose of graphic displays. For the construction of good graphs, there needs to be accurate in regards to the appropriate labelling, and scaling along with aggregation and problems pertaining to stratification. Summarizing the data. For the summarization of the data, a few of the typical summary statistics are included such as standard deviation, correlation, percentiles, and median, etc.. They’re considered amongst one of the more innovative summaries like principal components. Business Intelligence is considered to be a wider area for the making of decisions involving the use of data mining as a tool. With the support of Data mining, the data in business intelligence becomes more important for users. There exist, various kinds of data mining. They are inclusive of social network data mining, pictorial mining, web mining, relational databases, text mining, web mining, video data mining, etc.. All of these are implemented in the field of Business Intelligence.