Last month I introduced the concentric model that places meta data about master data, the most valuable data for an enterprise, at the center. As we move from the center, the model addresses the other types of meta data in terms of priority. Second in importance is the data warehouse meta data, then the processes and transformations involved in moving data to and through a data warehouse, and finally the application meta data.

Thinking of meta data this way helps us understand the reach of different types of meta data. This is useful for developing a meta data approach that recognizes the different business value of different classes of meta data. Second, a clear mental model for meta data is especially important to offset the void left by meta data tools available today. These tools often create meta data for the purpose of enabling a specific tool, such as an ETL tool or a query tool. However, there is a need for the creation of meta data that provides comprehensive documentation of enterprise data. A meta data model ensures that enterprises focus their efforts on the subset of meta data with the biggest business value.

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