Intelligent Technique to Determine Behavior of Dimension Tables in Semi-Star Schema Generation

Abstract

Data warehousing is gaining importance day by day in enterprises, as it helps them to improve their business intelligence. The process of creating a data warehouse needs to be automated so that the transactional sources are generated in least time, with maximum accuracy and with minimum dependability on users. The technique presented in this paper automates the process of converting database logical model into data warehouse logical model to generate semi-star schema by using artificial neural networks. More precisely, the step of differentiating dynamic behavior dimensions from static behavior dimensions has been automated by using feedforward backpropagation neural networks. This network ascertains dimensions which are sensitive to changes. The network is trained for all the possible values of inputs & outputs and has been tested for actual results.