Data Warehouse (DW) can be defined as a source of discussion of a project, a base analytical data that supports decision-making processes.  In this context, a method is a product for Mounting and data management from various sources in order to gain insight in a simple and detailed part of any business.

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One of the simplest concepts to define easily and clearly one DW is: “A copy of the data transactions, structured specifically for analysis and reporting”. But there are other concepts that may be used to characterize a DW:
– Is an analytical database that is used as a basis for SAD systems. It is planned to store large amounts of read-only data, providing intuitive access;
– A set of integrated databases and based on issues designed to support functions of the SAD, where each data unit is related to one point;
– DW is a process that brings together data from heterogeneous sources, including historical data and data external to meet the need for structured and ad-hoc queries, and analytical reports decision support;
– It is a process, not a product for mounting and data management from various sources for the purpose of getting a simple and detailed view of part of the whole deal.

The main purpose of a DW is to provide the necessary support for the transformation of a base data of an organization, often transactional, online and called operating bank Data OLTP (On-Line Transaction Processing), for a larger database that contains history all data of interest in the organization, called OLAP database (Online Analytical Processing) and also known as DW itself.

The DW is oriented to the main issues, themes or areas of business undertaking. Systems commercial classics are organized around enterprise applications. As an example it is possible to use the context of a supermarket company, applications can be purchase, inventory and sales of products. The main subjects can be a provider, cost analysis, and client. In all aspects of DW more important is the fact of being integrated, which occurs when data pass the operating environment-based applications for the DW.

Finally, OLTP systems source data are modified and converted to a uniform state to allow the load on the DW. The data input process in DW is conducted so that the many application inconsistencies are undone. It matters, for example, that the data the DW, used to represent male / female, are encoded as m / f or 1/0. what really matter is that apart from the encoding to be done DW, it should also be made consistently and regardless of the source application. If an application data are encoded as x / y, they will be converted as they are transferred to the DW. Thus, the DW becomes an important tool to aid decision making and macro view of business processes.

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