4.1 For Handling Multi-Dimensional QueriesInstead of recording the data in theform of relational database i.e. relational data model, multi – dimensionaldata model can be used. We can store the data in the form of data cubes, whichis able to handle the multi-dimensional queries.
Data cubes will be createdusing OLAP On-Line Analytical Processing (OLAP) is a method to support decisionmaking in situations where raw data on measures such as sales or profit needsto be analyzed at different levels of statisticalaggregation. In OLAP, queries are made against multidimensional cubes, calledOLAP cubes. 4.2 For HandlingSecurity FeaturesWe know that UML is very good modelingtool but not better for implementing the securityfeatures. As a solution of this problem use of Model-Driven Architectureapproach is proposed, which defines system functionality using a platform-independent model (PIM) using an appropriate domain-specific language (DSL).
One of the main aims of the MDA is toseparate design from architecture. As the concepts and technologies used torealize designs and the concepts and technologies used to realize architectureshave changed at their own pace, decoupling them allows system developers tochoose from the best and most fitting in both domains. 4.3 For HandlingResponse TimeCombination of Model-Driven Architecture approachwith data mining technique through OLAP will lead us to solve several businessproblems. The implementation will give the quick results for the complexqueries and it will also increase the performance of the system. In OLAP, queries are made against multidimensionalcubes, called OLAP cube queries fired against these will be fast.
Complex querieswill be handled easily and information will be available quickly.Multidimensional queries will be fired to get complex information which is noteasily possible with relational database query. 5. Work plan1. LiteratureSurvey: Six Months2. Solutionof Handling Multi-Dimensional Queries: Four Months3. Solutionof Handling Security Features: Three Months4. Solutionof Handling Response Time: Three Months5.
Solutionof Other Problems: Four Months6. ThesisWriting & Submission: Four Months 6. ConclusionMajorbenefit of our approach is that, once we have established the model-drivenarchitecture for both data under analysis and analysis techniques for datamining, analysts can model their data-mining related tasks easily.
Our work dealswith high-level mechanisms to specify data-mining related tasks. Model drivenengineering approach is used for mining the data from the data warehouse whichhelps us in many aspects.