A shared context approach for supporting experts in data ETL (Extraction, Transformation and Loading) processes

Abstract

Many experts in data integration often use standard procedures to accomplish the process of extracting data from the existing source systems in order to be transformed and loaded into new target systems such as a data warehouse or ERP (Enterprise Resource Planning) applications. The process is called ETL (Extraction, Transformation and Loading) process. There are different ways of applying such a process by different actors because they do not have the same viewpoints in the contexts in which the process occurs. To create an effective strategy and minimize risks, actors need to devote their efforts to develop new practices to meet the current business and IT needs, and mainly use past expert experience. The paper presents how to contextualize ETL processes based on different expert viewpoints. We show how making shared context explicit can help to improve the ETL process and, thus, avoid conflicts between experts having different viewpoints. We illustrate our proposal by using a software tool called Contextual Graphs (CxGs). The paper is intended to provide the basis for the development of an experience base that will be used by a support system for data migration experts.