Data mart designers are often asked whether the data mart will be for decision support or "dynamic" in nature. In this context, dynamic means that the data mart has several attributes (e.g., frequent updates, recalculation of data fields) which are thought to conflict with decision support requirements. The reality, however, is that the requirements of the data mart include dynamic characteristics if the business process supported by the data mart is fully considered. Therefore, the real decision to be considered is how to support this requirement. To fully explore this issue, let's consider a marketing data mart for a telecommunications firm. At first glance, the requirements for the telecommunications marketing data mart include ad hoc decision support, analytic capabilities, list extraction capabilities (e.g., pull lists of names for direct mail) and reporting, to name a few. The resulting solution would provide marketing users with the ability to analyze customer trends, target customers using expected response/value models, pull the names for the mail shop or telemarketing operation and analyze results on a campaign or customer segmentation basis. At this point, all the elements seem to be integrated in a solution that supports the direct marketing business process.

If we investigate further, however, we learn that nothing can be further from the truth. To demonstrate, let's focus on just one component of the business process--the analysis step. This step of the process provides the marketing user and organization with marketing promotion results information. To effectively provide this, the system needs to have all promotion-related information. At the most basic level, it must provide the answer to the question: Did person X respond to promotion Y? This requires the data to provide knowledge on who received promotion Y and what purchases or transactions are associated with person X. To provide this information in the database, dynamic characteristics must be supported!

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