This article introduces the concept of semantic enterprise and outlines a connection between semantic enterprise and master data management (MDM) concepts. The article also shows that successful transitioning to semantic enterprise requires significant improvements in enterprise metadata and especially in business metadata management. It explains the importance of supporting an enterprise-level semantic continuum from both business and IT communities by committing to development of enterprise architecture tenets that would bring both communities to a more synergetic environment.
Once broadly realized, the critical and indispensable nature of the relationship between business, information and technology architectures will generate demand for improvements to modeling tools that vendors will have to meet in order to remain relevant.
Master Data Management and Metadata
Currently, most tool vendors define MDM as the capability to create and maintain a single, authoritative physical source of “master” data. The purpose of this source is to make shared data – data that has a single content and format – available to all the enterprise systems that need to reference it. As such, master data is typically called reference data.1 (Some authors differentiate between reference and master data.)
While MDM, by this definition, is an important technical pursuit in its own right, there is a larger phenomenon behind it.
The broader issue is the semantic integrity of shared data (or rather, the lack of it), particularly at the enterprise level. “Lack of what Gartner calls semantic reconciliation among data from different sources is inherent in a diverse, dynamic and autonomous organization. Resolving discrepancies in metadata descriptions from multiple tools, not to mention cultural and historical differences, involves more than physically consolidating metadata into a common repository.”2
In other words, it is always possible, and arguably, quite easy, to misinterpret any shared data in the absence of rich contextual information that unambiguously distinguishes between different possible meanings. A substantial portion of this rich metadata context should come from information about the business processes that generate and use the shared data. While this metadata continuum starts in the business function model layer, it should support a consistent interpretation of shared metadata that continues through the complete business-IT space, all the way through to the implementation and maintenance of the deployed applications and services.
Consider a scenario where marketing, sales, and customer service departments all use the enterprise current customers set. In order for any enterprise to produce reconcilable financial and managerial reports, it is imperative that when systems from different departments access the same data from a single source, their interpretation of what constitutes “current customers” should also be identical. In the case of historically different definitions embedded in legacy systems, each department should be aware of which particular definition has been used for the enterprise master data and how to correlate that definition with its own departmental definition of current customer. The following architectural model helps to minimize probability of errors.
Three-Layered Architectural Model
A simple enterprise architecture model that supports the desired metadata layering is shown in Figure 1.3 This model links all three layers: business function, system specification and physical/implementation, into one enterprise metadata continuum, in order to guarantee information integrity for the whole enterprise.
All constituents that populate enterprise architecture models can be grouped into four architectural domains: business, information, application and infrastructure.4 Notice that according to the proposed partitioning, data architecture does not constitute its own domain but is actually a subdomain of information architecture.
Management of metadata information that describes the physical (infrastructure) layer is a challenging problem in its own right. However, this topic is well outside of this article’s scope and is extensively covered by the ITIL and numerous other publications on Configuration Management Database (CMDB). For those interested in a detailed discussion of the enterprise infrastructure metadata topic, please see Charles Betz’s “Architecture and Patterns for IT Service Management, Resource Planning, and Governance: Making Shoes for the Cobbler's Children”.5
