Holds multiple subject areas
Holds very detailed information
Works to integrate all data sources
Does not necessarily use a dimensional model but feeds dimensional models.
Often holds only one subject area- for example, Finance, or Sales
May hold more summarised data (although many hold full detail)
Concentrates on integrating information from a given subject area or set of source systems
Is built focused on a dimensional model using a star schema.
It is important to note that there are huge differences between these two tools though they may serve same purpose. Firstly, data mart contains programs, data, software and hardware of a specific department of a company. There can be separate data marts for finance, sales, production or marketing. All these data marts are different but they can be coordinated. Data mart of one department is different from data mart of another department, and though indexed, this system is not suitable for a huge data base as it is designed to meet the requirements of a particular department.
Data Warehousing is not limited to a particular department and it represents the database of a complete organization. The data stored in data warehouse is more detailed though indexing is light as it has to store huge amounts of information. It is also difficult to manage and takes a long time to process. It implies then that data marts are quick and easy to use, as they make use of
small amounts of data. Data warehousing is also more expensive because of the same reason.