ETL Process Modeling Conceptual for Data Warehouses: A Systematic Mapping Study

Abstract

BACKGROUND: A data warehouse (DW) is an integrated collection of subject-oriented data in the support of decision making. Importantly, the integration of data sources is achieved through the use of ETL (Extract, Transform, and Load) processes. It is therefore extensively recognized that the appropriate design of the ETL processes are key factors in the success of DW projects. OBJECTIVE: We assess existing research proposals about ETL process modeling for data warehouse in order to identify their main characteristics, notation, and activities. We also study if these modeling approaches are supported by some kind of prototype or tool. METHOD: We have undertaken a systematic mapping study of the research literature about modeling ETL processes. A mapping study provides a systematic and objective procedure for identifying the nature and extent of the available research by means of research questions. RESULTS: The study is based on a comprehensive set of papers obtained after using a multi-stage selection criteria and are published in international workshops, conferences and journals between 2000 and 2009. CONCLUSIONS: This systematic mapping study states that there is a clear classification of ETL process modeling approaches, but that they are not enough covered by researchers. Therefore, more effort is required to bridge the research gap in modeling ETL processes.