Enterprise Data Warehouse is a centralized warehouse which provides service for the entire enterprise. A data warehouse is by essence a large repository of historical and current transaction data of an organization. An Enterprise Data Warehouse is a specialized data warehouse which may have several interpretations.

Several terms used in information technology have been used by a so many different vendors, IT workers and marketing ad campaigns that has left many confused about what really the term Enterprise Data Warehouse means and what makes it different from a general data warehouse.

Enterprise Data Warehouse has emerged from the convergence of opportunity, capability, infrastructure and need for data which has exponentially increased during the last few years as technology has advanced too fast and Business Enterprises tried to do their best to catch up and be on the top of the industry competition.

In order to give a clear picture of an Enterprise Data Warehouse and how it differs from an ordinary data warehouses, five attributes are being considered. This is not really exclusive they bring people closer to a focused meaning of the Enterprise Data Warehouse from among the many interpretations of the term. These attributes mainly pertain to the overall philosophy as well as the underlying infrastructure of an Enterprise Data Warehouse.

The first attribute of an Enterprise Data Warehouse is that it should have a single version of truth and that entire goal of the warehouse’s design is to come up with a definitive representation of the organization’s business data as well as the corresponding rules. Given the number and variety of systems and silos of company data that exist within any business organization, many business warehouses may not qualify as an Enterprise Data Warehouse.

The second attribute is that an Enterprise Data Warehouse should have multiple subject areas. In order to have a unified version of the truth for an organization, an Enterprise Data Warehouse should contain all subject areas related to the enterprise such as marketing, sale, finance, human resource and others.

The third attribute is that an Enterprise Data Warehouse should have a normalized design. This may be an arguable attribute as both normalized and de-normalized databases have their own advantages for a data warehouse. In fact, may data warehouse designers have used denormalized models such as star or snowflake schemas for implementing data marts. But many also go for normalized databases for an Enterprise Data Warehouse in the consideration of flexibility first and performance second.

The fourth attribute is that an Enterprise Data Warehouse should be implemented as a Mission-Critical Environment. The entire underlying infrastructure should be able to handle any unforeseen critical conditions because failure in the data warehouse means stoppage of the business operation and loss of income and revenue. An Enterprise Data Warehouse should have high availability features such as online parameter or database structural changes, business continuance such as failover and disaster recovery features and security features.

Finally an Enterprise Data Warehouse should be scalable across several dimensions. It should expect that a company’s main objective is to grow and that the warehouse should be able to handle the growth of data as well as the growing complexities of processes which will come together with the evolution of the business enterprise.

Because of the fast evolution of information technology, many business rules have been changed or broken to make way for rules which are data driven. Processes may fluctuate from simple to complex and data may shrink or grow in the constantly changing enterprise environment. Hence, a real Enterprise Data Warehouse should scale to these changes.