The rationale of enterprise
business intelligence is to discover the utilization of capital assets within the organization.
The current level of technology can deliver knowledge to the end user, but more advanced
methods are needed in the areas of taxonomies, ontologies, standards, and automation. Most
researchers will agree that a broadly-based approach is needed, including consideration of
how users understand, navigate, and communicate knowledge embodied in computer-based
vocabularies and metadata classification schemes. Implementations of structured metadata
solutions must overcome a variety of problems including: mixed vocabularies, content and
structure of the meta-model, the variety of asset structures, and integration of less structured
knowledge placed in documents, business processes, and Web pages.
Figure 1 presents a layered view of the role enterprise metadata plays in the communication
of knowledge via enterprise business intelligence. The enterprise architecture defines
a universe that consists of assets that are created by the technical community in a variety of
forms (Layer 1). An asset is any person, place, or thing within the technological community.
Examples of assets include: databases, logical models, physical models, XML structures,
components, documents, metrics, systems, interfaces, and so forth.
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