Expedition for the Exploration of Apposite Knowledge

Once we have the organized collection of data, typically in digital form, we try to move from operational aspect towards the analytical one wherein the users who are the actual Knowledge workers and take the strategic decisions are of more importance, in contrast to the users who work on the operational aspect of a big system and take the tactical decisions. Now, if the application domain is changed from operational data management to data management for strategic purposes, we need to change the data base design as well, keeping the dynamic nature into consideration. So, Information providing service is the first point of concern for knowledge extraction. The ever increasing interest in the knowledge discovery made us to move the data from the statistical aspect towards designing creative algorithms in an attempt to find out the possible efficient solution so as to make strategic decisions as proper as possible. The aim of the paper is to present a Data Warehouse architecture that focuses on recent updation in the OLTP systems, in addition to the basic ELT/ETL process. Further, the paper discusses a wide range of knowledge discovery techniques used to extract fresh knowledge out of the data present in such a Real-Time Data Warehouse. The future research direction in the field has also been mentioned.