DWH vs DataMart

A data warehouse is a central repository for all or significant parts of the data that an enterprise's various business systems collect. Enables strategic decision making.

A data mart is a repository of data gathered from operational data and other sources that is designed to serve a particular community of knowledge workers. In scope, the data may derive from an enterprise-wide database or data warehouse or be more specialized. The emphasis of a data mart is on meeting the specific demands of a particular group of knowledge users in terms of analysis, content, presentation, and ease-of-use. Users of a data mart can expect to have data presented in terms that are familiar.
In practice, the terms data mart and data warehouse each tend to imply the presence of the other in some form. However, most writers using the term seem to agree that the design of a data mart tends to start from an analysis of user needs and that a data warehouse tends to start from an analysis of what data already exists and how it can be collected in such a way that the data can later be used. A data warehouse is a central aggregation of data (which can be distributed physically); a data mart is a data repository that may derive from a data warehouse or not and that emphasizes ease of access and usability for a particular designed purpose.

DataWareHouse:
•Corporate/Enterprise-wide
•Union of all data marts
•Data received from staging area
•Queries on presentation resource
•Structure for corporate view of data
•Organized on E-R Model.

DataMart:
•Departmental
•A Single business process
•STAR join(facts and Dim)
•Technology optimal for data access and analysis
•Structure to suit the departmental view of data

Summary:

DataMart is subject oriented. When you start designing warehouse for a bank, You will have lot of subjects to take-care under single roof. For instance, Insurance, Transactions, Mortgages etc..Each title is a subject which will have its own DataMart.