Diverse types of Data Warehouse
Different Enterprise Organizations are using Data Warehousing techniques to handle their business. Data warehouse technique is applied according to size and nature of the transaction of the organization.A data mart contains a subset of corporate-wide data that is of value to a specific group of users.Depending on the source of data, data marts can be categorized as independent or dependent.
Different Enterprise Organizations are using Data Warehousing techniques to handle their business. Data warehouse technique is applied according to size and nature of the transaction of the organization. The diverse data warehouse are listed below
An enterprise warehouse collects all of information about the subject spamming 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 well as summarized data, and can range in size from few gigabytes to hundreds of gigabytes, terabytes or beyond. An enterprise data warehouse may be implemented on traditional mainframes, UNIX super servers or parallel architecture platforms. It requires extensive business modeling and may take years to design and build.
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 , marketing data mart may confine its subject to custom to customer, item, and sales. The data contained in data mart tends to be summarized.
Data marts are usually implemented on low cost department servers that are UNIX or Windows/NT 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 from data captured from one or more operational systems or external information providers, or from data generated locally within a particular department or geographic area. Depending data marts are sourced directly from enterprise data warehouse.
A virtual warehouse is 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.
The top-down development of an enterprise warehouse serves as a systematic solution and minimum integration problems. However, it is expensive, takes a long time to develop, and lacks flexibility due to the difficulty in achieving consistency and consensus for a common data model for the entire organization. The bottom-up approach to design, development, and deployment of independent data marts provides flexibility, low cost, and rapid return of investment. It however, can lead to problems when integration various disparate data marts into a consistent enterprise.
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