Purpose -The application landscapes of major companies all have their own complex structure. Data have to be exchanged between or distributed to the various applications. Systemizing different data integration patterns on a conceptual level can help to avoid uncontrolled redundancy and support the design process of data integration solutions. Each pattern provides a solution for certain data integration requirements and makes the design process more effective by reusing approved solutions. Proposes identifying these patterns. Design/methodology/approach -After a broad literature review data were obtained from interviews and documentary sources. Ten semi-structured interviews were conducted within four different companies operating in the financial service industry. EAI-and IT-architects as well as project managers and CTOs were involved in these interviews. Findings -Five different data integration patterns were identified. Solutions for upcoming data integration requirements can be designed using these patterns. Advantages and disadvantages as well as typical usage scenarios are discussed for each identified data integration pattern. Research limitations/implications -In order to identify data dependencies, to detect redundancies and to conduct further investigations, a consistent methodology for the description of application landscapes has to be developed. The presented design patterns are one part of this methodology only. The approach in this paper only considers data integration while in reality there are also other integration requirements like functional or process-oriented integration. Practical implications -The identified design patterns help practitioners (e.g. IT-architects) to design solutions for data integration requirements. They can map the conceptual patterns to company specific technologies or products to realize the solution physically. Originality/value -The design patterns are indifferent from any technology or products which ensure a broad application. Business requirements (e.g. requirement for autonomous processing) are considered first when designing a data integration solution.
Current concepts of enterprise application integration often focus on technical issues only. Previous, more holistic approaches of deriving information system concepts from business requirements often addressed the development of a new information system replacing the existing, not integrated systems. In this paper, we describe an extension of the Business Engineering framework for application integration purposes.
Die Effektivität und Effizienz des Informationssystems der Unternehmung werden wesentlich vom Integrationsgrad der Applikationen beeinflusst. Um den Integrationsgrad systematisch planen und steuern zu können, muss ein entsprechendes Zielsystem spezifiziert werden. Dazu werden in diesem Beitrag fünf Ziele der Applikationsintegration identifiziert. Zu den einzelnen Zielen werden jeweils Kennzahlen diskutiert, die eine Messung der Zielerreichung ermöglichen. Zudem werden Abhängigkeiten und Wechselwirkungen zwischen einzelnen Zielen qualitativ untersucht und daraus Hypothesen abgeleitet.
The effectiveness and efficiency of information systems are closely related to the degree of integration between applications. In order to support the management of application integration, five success factors are analyzed. For each success factor, appropriate performance indicators are proposed. Since the analysis indicates that the success factors are closely interrelated, these dependencies are discussed and hypotheses are derived.
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