Data Mining processing using GRID technologies

Daryl Pregibon - Google Inc. Research Scientist states that: "Data Mining is a mixture of statistics, artificial intelligence and database research." In other words, the purpose of this process is the automatic discovery of knowledge hidden in data using various computational techniques. The purpose of this work is represented by the analysis of the impact of GRID technology for storing and processing large amounts of information and knowledge. Using computational power of computers and the most effective means of working with data, information exploitation is no longer a difficulty. It shows a strong expansion of the use of GRID technologies in various fields, as a consequence of the development of our society and, in particular, of the scientific and technical world that require technologies that allow all parties to use resources in a well-controlled and well organized way. Therefore, we can use GRID technologies for Data Mining processing. To see what the data "mining" process consist of, we must go through the following steps: construction and validation of the model and application of the model to new data. GRID - Data Mining connection can be successfully used to monitor environmental factors in environmental protection field, in civil engineering field to monitor the behavior in time, in medical field to determine diagnoses, in telecommunications. To be able to develop "mining" applications of the distributed data within a GRID network, the infrastructure that will be used is the Knowledge GRID one. This high level infrastructure has an architecture dedicated to data "mining" operations and specialized services for resource discovery stored in distributed deposits, information services management. In this concept, the achievement of data storage and processing is one of the most effective ways one can obtain results with high accuracy, according to initial requirements, using the automated knowledge discovery principles from the entire resource of knowledge existing in different systems. We can say that the main benefit obtained by using Knowledge GRID architecture is a major improvement in the execution speed of the "mining" process.