By R. A. Moeller
Flip to this booklet to profit to control mountains of data
through disbursed information warehousing ideas.
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Example text
Most of the concepts discussed are applicable to all three forms. A homogeneous distributed data warehouse has multiple data collections; it integrates multiple data resources. The homogeneous system resembles a centralized data warehouse, but instead of storing all the data at one site, the data is distributed across a number of sites in the network. Each of these sites can have its own autonomous database and is capable of functioning as an independent data mart. , database product) is used at each site, usually relational technology.
It specifies the location of each fragment, functioning as a "router" for the distributed system. It supports the possibility of data replication within the system by allowing the fragments to exist at more than one site. When replication is present, an optimizer selects the most efficient access path. The heterogeneous distributed data warehouse system (see Figure 2-10) is characterized by the use of different DBMSs at the local sites. While most of these locations function as independent data marts, it is possible to include other data sources, even external ones (via the Internet).
However, a comprehensive enterprise data model is an expensive and timeconsuming project, and the corporation may not be willing to spend either the time or money before seeing some tangible return on investment. Often, the designer is forced to proceed without the benefit of any data model. While it is possible to successfully design and implement a data mart without a model, this brings an element of risk to the project that it would be better to avoid. At the very least, the enterprise data model/metadata must be developed concurrently with the data marts' projects.