By JuergenKress on Apr 06, 2014
Introduction "You will waste your investment in SOA unless you have enterprise information that SOA can exploit." – Gartner
This quote from Gartner, Inc. describes the relationship between service-oriented architecture (SOA) and master data management (MDM) very vividly. An essential principle behind SOA is the reuse of components and the flexibility of using these components to support new functionalities or processes. MDM provides universal components (or services) for consistent data maintenance and distribution. Here the architecture concepts and principles of SOA run into MDM.
This article begins by giving a brief motive for using MDM and a conceptualization. It will then go on to present typical variants for possible MDM architecture concepts, and illustrate the interplay of MDM and SOA with reference to the architecture pattern.
Increasing pressure from competition means that business models and underlying business processes have to be adapted in ever shorter cycles. At the same time, globalization and the digital networking of companies are making interaction with external business partners even more complex. Securely exchanging high-quality data is crucial for increasing efficiency in processes. This is where the central issue, the quality of information, and therefore its security in transactions, evaluations, and reports, all stem from. Once a company is no longer in a position to provide a consistent and consolidated view of its central business objects, implementing a company-wide policy for master data management becomes a good idea.
Unfortunately, in many companies today it is common for IT systems to be unable to keep up with fast changes in organization, business, and even technology. As a result, on the companies' side, a vast, ever-growing web of IT systems with known integration problems comes into being. This heterogeneity accounts for a variety of challenges when using master data that include differences in:
- data structures and formats in master data
- specifications and understanding of the master data values in the participating organizational units
- validations and plausibilities (data quality)
- processes and responsibilities concerning data sovereignty (data governance)
- business processes with partially conflicting functionalities in the application systems
- organizational units that have different systems for master data maintenance
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