Ontology and Hyper Graph Based Dashboards in Data Warehousing Systems
Analytical and computational requirements are increasing in data warehousing systems. So it is very crucial to identify semantically equivalent data, linking them and discovering structural dependencies. This can be performed using dashboards. Dynamic dashboard will perform the customization of information for specific need of user. And we are using an improved method for dashboard development using hyper graph approach and ontology exploration. Existing dashboard design satisfies given user query and provides flexibility in changing user interactions. In this paper a quick specification of dashboard interfaces is obtained for detailed DB (data base) query language where semantics of user interaction is in a declarative manner. Keyword- QBSE, QBVE, Ontology, Dashboard, Hyper graph, DBE I. INTRODUCTION The variety, complexity and diversity of analytical requirements lead to increased interest of on-demand DWH systems(data warehousing systems)(1),where qualitative difference in data monitoring, exploration and other tasks is obtained by interactive and analytical data processing. This maximized the popularity of dashboard applications which analyze and monitor flexible, rapid information for specific need of users (2).Performance and flexibility in the dash board development process is maintained by the QBE method based on knowledge. Ontological knowledge is utilized by DBE framework to formalize the context and content of heterogeneous sources of data. DBE query language defines queries on data source's base attributes, base data semantics which is ontology encoded and on the analyzed data and the Ontology data connections . Ontology explorations associated with hyper graph transversals problem (3). Here hyper graph clustering and hyper graph partitioning techniques are used (4) which provide rich information sources for data linkage and semantic browsing tasks. Dashboard is an easily readable, real-time user interface, can be viewed as a single page. It includes current status and organization's historical trends which are presented graphically thus instantaneous and important decisions can be made at a glance. In computer and information science, ontology is representing knowledge as concept sets within a domain and different relationships among concept pairs. We are describing our method using a real-world based scenario and explaining the benefits regarding the solution's design flexibility.