A data warehouse can define as a repository that can be accessed to retrieve information of an organization's electronically stored data, designed to facilitate reporting and analysis.
When we go to the history of data warehouse we can define the concept of data warehousing dates back to the late 1980s .The concept of data warehousing was reviled when IBM researchers Barry Devlin and Paul Murphy developed the business data warehouse. In essence, the data warehousing concept was intended to provide an architectural model for the flow of data from operational systems to decision support environments.
Data warehouse is a subject-oriented, integrated, time-variant, non-volatile collections of data used to support analytical decision making. When we further explore we can identify that data warehouses are physically separated from operational systems, even though the operational systems feed the Warehouse with source data. Anywhere Data warehousing concept was intended to provide an architectural model for the flow of data from operational systems to decision support environments. The concept attempted to address the various problems associated with this flow, mainly the high costs associated with it. We can demonstrates how the data warehouse serves as a facilitator to retrieve data from any source such as independent databases and their external interfaces as follows.
When we go though the data warehouse we can identify following purposes,
Multiple angles:This allows viewing data from multiple angles (dimensions). We can identify this as one of the best aspects of the Data warehouse.
Providing an adaptive and flexible source of information: Data Warehouse has the capabilities to adapt quickly to the changing requirements. So it is really easy to handle the necessary changers when it needed. That’s why we can say that it is adaptive and flexible metherod for the source of information
Establish the foundation for Decision Support: We all know that decisioning process of an organization will involve analysis, data mining, forecasting, decision modeling etc. So by having a common point that allows to provide consistent, quality data with high response time provides the core enabler for making fast and informed decisions.
All systems into one environment: We all know that in enterprise environment which may have many systems of record. The data warehouse allows to aggregate all systems into one environment.
Keeping Analysis/Reporting and Production Separate: Data ware aids to keep analysis/reporting (non-production use data) separate from production data. So this can identify as one of purpose of implementing a data warehouse
Data Consistency and Quality :It is common that organizations are riddled with different types of important systems from which their information comes. Each of these systems may carry the information in different formats and also may be having out of synch information. So by bringing the data from these disparate sources at a common place, one can effectively undertake to bring the uniformity and consistency in data