In my April column, I introduced a model of concentric rings of value to prioritize meta data development. In May, I provided more complete definitions of the contents of the rings. In this column, I will discuss the constraints we face with today's development tool environment as well as some ideas concerning prioritizing meta data development around the tools you have in house.

As a quick summary: In the data warehouse tradition, meta data has been classified as either business meta data or technical data. For data warehousing purposes, meta data has tended to be limited to data definitions, data sourcing and business rules for data transformations. However, historically meta data included all the technical data needed to define application systems, especially OLTP applications. That broader scope of meta data included business rules and requirements, data definitions and relationships, and application components and relationships. The overhead for developing and maintaining this complete view of meta data using a passive data dictionary was approximately 15 percent of the effort to design and build an application. This cost exceeded the value of the meta data as proven by the sporadic existence of meta data supporting corporate systems today.

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