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

Virtual 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:

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.

Enterprise Warehouse:

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.