Download PDF by John Poole, Dan Chang, Douglas Tolbert, David Mellor: Common warehouse metamodel: an introduction to the standard

By John Poole, Dan Chang, Douglas Tolbert, David Mellor

The respectable advisor to programming with the innovative data-sharing technologyThe universal Warehouse Metamodel (CWM) is the recent OMG commonplace that makes the sharing of knowledge seamless. The CWM normal improvement staff presents builders with a whole review of what CWM is and the way it really works. After acquainting readers with the CWM structure and the way each one CWM part suits into current database and knowledge warehouse architectures, the authors offer professional suggestions on how you can plan for, enforce, and install CWM technologies.Companion website positive factors updates on CWM applied sciences, descriptions of instruments, and hyperlinks to seller websites.

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Contrary to Kimball’s prediction, however, it appears highly likely that CWM will indeed become the universal meta data standard for data warehouse integration. The creators of CWM are confident that this is the case, not only because of the power and expressiveness of CWM, but also due to the compelling economic issues surrounding meta data integration. Data warehousing and business analysis product vendors can no longer afford to ignore this issue. David Marco in Building and Managing the Meta Data Repository: A Full Life Cycle Guide, provides a thorough analysis of the economic aspects of meta data and its ultimate effect on ROI.

This strategy ultimately determines the overall meta data technical architecture, which follows directly from the meta data management strategy, as well as the tools selected for implementing the meta data integration architecture. The meta data technical architecture (component 10) defines how the meta data management strategy is physically realized. It defines the specific meta data integration and interconnection topology, such as point-to-point, huband-spoke, or federated network. The architecture also defines the distribution of various meta data services to specific points in the topology.

A relational table has a name. A column has a name and a data type. The data type is specified as a string whose value denotes the data type (for example, “integer”). A table may contain any number of columns, as indicated by the association line joining the table to the column. The ‘*’ on the column end of the line denotes zero or more occurrences of column, and the black diamond and the ‘1’ at the table end denotes a column as being owned by precisely one table. Note that this relational table model does not describe any particular relational table, but rather describes how relational tables are defined.

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