Automatically Data Mining In Telecom Business

There are too much data but not enough information; this is a problem facing many telecom businesses. Most telecom businesses have an enormous amount of data, with a great deal of information hiding within it, but it is hard to analyze with the traditional methods of data analysis. Data mining provides a way to get at the information buried in the data. Data mining creates models to find hidden patterns in large, complex collections of data, patterns that sometimes elude traditional statistical approaches to analysis because of the large number of attributes, the complexity of patterns, or the difficulty in performing the analysis.Data mining functions can be divided into two categories: supervised (directed) and unsupervised (undirected). Supervised functions are used to predict a value; they require the specification of a target (known outcome). Targets are either binary attributes indicating yes/no decisions (buy/don't buy, churn or don't churn, etc.) or multi-class targets indicating a preferred alternative (color of sweater, likely salary range, etc.). Naive Bayes for classification is a supervised mining algorithm. Unsupervised functions are used to find the intrinsic structure, relations, or affinities in data. Unsupervised mining does not use a target. Clustering algorithms can be used to find naturally occurring groups in data.Oracle Data Mining (ODM) embeds data mining within the Oracle database. This article says the information about Data Preparation and Modeling , and describe the way to use PL/SQL procedure in Automatically Data Mining...