A Model-Driven Heuristic Approach for Detecting Multidimensional Facts in Relational Data Sources

Download Now
Provided by: Springer Healthcare
Topic: Big Data
Format: PDF
Facts are multidimensional concepts of primary interests for knowledge workers because they are related to events occurring dynamically in an organization. Normally, these concepts are modeled in operational data sources as tables. Thus, one of the main steps in conceptual design of a data warehouse is to detect the tables that model facts. However, this task may require a high level of expertise in the application domain, and is often tedious and time-consuming for designers. To overcome these problems, a comprehensive model-driven approach is presented in this paper to support designers in: obtaining a CWM model of business-related relational tables, determining which elements of this model can be considered as facts and deriving their counterparts in a multidimensional schema.
Download Now

Find By Topic