Intelligent granular approach to the integrated data bases management

Abstract

The main goal of our paper is the development of the new intelligent approach to the Big Data Bases data management and analysis, associated with the different types of data mathematical models. The presented circumstances are produce the sufficient problems for the information request implementation and the long-duration processes during the data analysis. One of the problems of this paper is the hybrid granulation data model development for the heterogeneous kinds of data. Also, the NoSQL request generation to the granulated data are considered. As a result, the new hybrid technique was developed for the uniformed read/write request and data analysis for the heterogeneous data content. The presented technique are the hybrid crisp/fuzzy approach for the data natural compressing during the hard disk operations.