Data Warehouse Models in Data Mining
From the perspective of data warehouse architecture, we have the following data warehouse models –
1. Virtual Warehouse
2. Data mart
3. Enterprise Warehouse
The view over an operational data warehouse is known as a virtual warehouse. It is easy to build a virtual warehouse. Building a virtual warehouse requires excess capacity on operational database servers.
Data mart contains a subset of organization-wide data. This subset of data is valuable to specific groups of an organization. In other words, we can claim that data mart contains data specific to a particular group.
Characteristics of Data mart:
1. Window-based or Unix/Linux-based servers are used to implement data marts. They are implemented on low-cost servers.
2. The implementation data mart cycles are measured in short periods, i.e, in weeks rather than months or years.
3. The life cycle of a data mart may be complex in the long run if its planning and design are not organization-wide.
4. Data marts are small in size.
5. Data marts are customized by the department.
6. The source of a data mart is a departmentally structured data warehouse.
7. Data marts are flexible.
An enterprise warehouse collects all the information and the subjects spanning an entire organization.
i. It provides us with enterprise-wide data integration.
ii. The data is integrated from operational systems and external information providers.
iii. This information can vary from a few gigabytes to hundreds of gigabytes, terabytes or beyond.