Data Warehouse Configurations

A Data Warehouse configuration, also known as the logical architecture, includes the following components:

- one Enterprise Data Store (EDS) - a central repository which supplies atomic (detail level) integrated information to the whole organization.

- (optional) one Operational Data Store - a "snapshot" of a moment in time's enterprise-wide data

- (optional) one or more individual Data Mart(s) - summarized subset of the enterprise's data specific to a functional area or department, geographical region, or time period

- one or more Metadata Store(s) or Repository(ies) - catalog(s) of reference information about the primary data. Metadata is divided into two categories: information for technical use, and information for business end-users.

The EDS is the cornerstone of the Data Warehouse. It can be accessed for both immediate informational needs and for analytical processing in support of strategic decision making, and can be used for drill-down support for the Data Marts which contain only summarized data. It is fed by the existing subject area operational systems and may also contain data from external sources. The EDS in turn feeds individual Data Marts that are accessed by end-user query tools at the user's desktop. It is used to consolidate related data from multiple sources into a single source, while the Data Marts are used to physically distribute the consolidated data into logical categories of data, such as business functional departments or geographical regions. The EDS is a collection of daily "snapshots" of enterprise-wide data taken over an extended time period, and thus retains and makes available for tracking purposes the history of changes to a given data element over time. This creates an optimum environment for strategic analysis. However, access to the EDS can be slow, due to the volume of data it contains, which is a good reason for using Data Marts to filter, condense and summarize information for specific business areas. In the absence of the Data Mart layer, users can access the EDS directly.

Metadata is "data about data," a catalog of information about the primary data that defines access to the Warehouse. It is the key to providing users and developers with a road map to the information in the Warehouse. Metadata comes in two different forms: end-user and transformational. End-user metadata serves a business purpose; it translates a cryptic name code that represents a data element into a meaningful description of the data element so that end-users can recognize and use the data. For example, metadata would clarify that the data element "ACCT_CD" represents "Account Code for Small Business." Transformational metadata serves a technical purpose for development and maintenance of the Warehouse. It maps the data element from its source system to the Data Warehouse, identifying it by source field name, destination field code, transformation routine, business rules for usage and derivation, format, key, size, index and other relevant transformational and structural information. Each type of metadata is kept in one or more repositories that service the Enterprise Data Store.

While an Enterprise Data Store and Metadata Store(s) are always included in a sound Data Warehouse design, the specific number of Data Marts (if any) and the need for an Operational Data Store are judgment calls. Potential Data Warehouse configurations should be evaluated and a logical architecture determined according to business requirements.