IJSRP, Volume 5, Issue 3, March 2015 Edition [ISSN 2250-3153]
Rajendra Desale ,Vaibhav Patil , Tushar Aware
Traditional DBSMs are suited for applications in which the structure, meaning andcontents of the database, as well as the questions to be asked are already well understood. There is, however, a class of applications that we will collectively refer to as Interactive Data Exploration (IDE) applications, in which this is not the case. IDE is akey ingredient of a diverse set of discovery-oriented applications we are dealing with, including ones from scientific computing, financial analysis, evidence-based medicine, and genomics. The need for effective IDE will only increase as data are being collected at anunprecedented rate. IDE is fundamentally a multi-step, non-linear process with imprecise end-goals. For example, data-driven scientific discovery through IDE often requires non-expert users to iteratively interact with the system to make sense of and to identifyinteresting patterns and relationships in large, amorphous data sets.