摘自《Data Mining - Concepts and Techniques》
Fromthe architecture point of view, there are three data warehouse models: the enterprise warehouse, the data mart, and the virtual warehouse.
Enterprise warehouse: An enterprise warehouse collects all of the information about subjects spanning the entire organization. It provides corporate-wide data integration, usually from one or more operational systems or external information providers, and is cross-functional in scope. It typically contains detailed data as well as summarized data, and can range in size from a few gigabytes to hundreds of gigabytes, terabytes, or beyond. An enterprise data warehouse may be implemented on traditional mainframes, computer superservers, or parallel architecture platforms. It requires extensive business modeling and may take years to design and build.
Data mart: A data mart contains a subset of corporate-wide data that is of value to a specific group of users. The scope is confined to specific selected subjects. For example, a marketing data mart may confine its subjects to customer, item, and sales. The data contained in data marts tend to be summarized. Data marts are usually implemented on low-cost departmental servers that are UNIX/LINUX- or Windows-based. The implementation cycle of a data mart is more likely to be measured in weeks rather than months or years. However, it
may involve complex integration in the long run if its design and planning were
not enterprise-wide. Depending on the source of data, data marts can be categorized as independent or dependent. Independent data marts are sourced fromdata captured fromone or more operational systems or external information providers, or fromdata generated locally within a particular department or geographic area. Dependent data marts are sourced directly from enterprise data warehouses.
Virtual warehouse: A virtual warehouse is a set of views over operational databases. For efficient query processing, only some of the possible summary views may be materialized. A virtual warehouse is easy to build but requires excess capacity on operational database servers.
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