What is Datamart???

Reference From: http://www.learn.geekinterview.com/data-warehouse/data-marts/what-is-data-mart.html

Data Mart is a subset of the data resource, usually oriented to a specific purpose or major data subject, that may be distributed to support business needs. The concept of a data mart can apply to any data whether they are operational data, evaluational data, spatial data, or metadata.

A data mart is a repository of a business organization's data implemented to answer very specific questions for a specific group of data consumers such as organizational divisions of marketing, sales, operations, collections and others. A data mart is typically established as one dimensional model or star schema which is composed of a fact table and multi-dimensional table.
In comparison, a data warehouse is also a repository of organizational data implemented as a single repository serving enterprise wide data across many if not all subject areas. The data warehouse is the authoritative repository at atomic level of all fact and dimensional data.

Despite some arguments on the similarity or difference between a data mart and a data warehouse, many still consider a data mart as specialized version of a data warehouse.

Advantage of Data Mart:
The data mart, like the data warehouse, can also provide a picture of a business organization's data and help the organizational staff in formulating strategies based on the aggregated data and statistical analysis of industry trends and patterns as well as part business experiences.

The most notable difference of a data mart from a data warehouse is that the data mart is created based on a very specific and predefined purpose and need for a grouping of certain data. A data mart is configured such that it makes access to relevant information in a specific area very easy and fast.

Within a single business organization, there can more than one data mart. Each of these data marts is relevant or connected in some way to one or more business units that its design was intended for. The relationship among many data marts within a single company may or may not involve interdependency.

They may be related to other data marts if they were designed using conformed facts of dimensions. If one department has a data mart implementation, that department is considered to be the owner of the data mart and it owns all aspects of the data mart including the software, hardware and the data itself. This can help manage data in a huge company by having a modularization method such that a department should only manipulate and develop its own data as they see if without having to alter data from other department's data marts. Then other departments need data from the data mart owned by a certain department, proper permission should be asked first.

In other data mart implementation where there is strict conformed dimension, some shared dimensions exist such as customers and products and business ownership will no longer apply.

Data marts can be designed with star schema, snowflake schema or starflake schema. The star schema is the most simple of all the styles related to data mart and data warehousing. It consists only of few fact tables.

The snowflake schema is a variation of the star schema and the storage method is of multidimensional nature. The starflake schema is a hybrid mixture of both the star and snowflake schemas.

Data marts are especially useful to make access to specific frequently access data very ease. It can give a collective picture or a certain aspect in the business by a specific group of users. Since data marts are smaller compared to a full data warehouse, response time could be lesser and the cost of implantation could also be less expensive.