Data Integration Patterns in the Context of Enterprise Data Management

Enterprise Data Management comprises various tasks such as providing the strategies, concepts, infrastructure, and tools for OLTP (Online Transaction Processing) and OLAP (On-line Analytical Processing). One important factor is the data integration so that different IT systems are able to exchange transactional and analytical data in a controlled and consistent manner. In the case of OLTP, different options are possible, e. g. direct coupling of systems that lead to uni- or bi-directional integration. However, when multiple systems have to collaborate, a dedicated enterprise data management system might be considered. A premise for this solution is a normalized, consolidated enterprise data model that covers all data or entity models of the systems that are to be integrated. Data Integration Patterns help the business analyst, data scientist, and other IT experts to discuss, document, and conceptualize such an enterprise data model and the data integration tasks. This paper presents Data Integration Patterns for OLTP in the context of the integration of data-intensive IT systems with the goal to use an enterprise data management system. Because Enterprise Data Management is tightly coupled with Enterprise Integration Management, the Data Integration Patterns presented in this paper are also discussed in conjunction with Enterprise Integration Patterns.