|M.Sc Student||Feldman Roman|
|Subject||Designing Data Warehouse with Object-Process Methodology|
|Department||Department of Computer Science||Supervisor||Professor Dov Dori|
Data warehouse modeling is a complicated task, which involves knowledge of business processes, as well as familiarity with operational information systems structure and behavior. Several modeling techniques were suggested to utilize the operational system structural or behavioral model in order to construct a data warehouse conceptual model. Our analysis of these methods indicates that they are limited in their applicability to model large-scale systems, as they require acquaintance with the business processes and ability to select relevant transactional entities. These techniques usually disregard the process perspective and require multiple manual actions, as discovering measures and relevant dimensional entities are unassisted.
To overcome the limitations of existing techniques, we propose OPM-based Data Warehouse Construction (ODWC), a method based on Object-Process Methodology (OPM) for constructing a data warehouse model. OPM was the modeling method of choice primarily because it unifies all system aspects within its single view. The method uses both the structural and behavioral aspects of the underlying operational system to create a multidimensional conceptual data warehouse model. Assisted by a software tool, we apply the ODWC method on several case studies, utilizing the semantic features of OPM to achieve the task at hand. To evaluate the method, we compare the resulting model to models obtained using other methods and real-life models, demonstrating that ODWC overcomes important limitations these methods present. Our comparison shows that the ODWC method is the most suitable for the task of transforming operational system specification to a data warehouse model for the following reasons: (1) OPM’s scaling mechanisms allow presenting the operational system and the supported business processes at varying levels of abstraction. This feature aids selection of the business process to be analyzed, and allows creating cubes at different summation levels. (2) OPM allows distinction of the business objects relevant to the business functionality. (3) OPM enables clear identification of the outcomes of a business process.