Twelve Rules That Define a Data Warehouse*
In 1994, William H. Inmon and Chuck Kelley created a list of twelve rules defining a Data Warehouse. Although we have already established their substance in previous discussions, the Inmon/Kelley list summarizes these discussions well:
- The Data Warehouse and operational environments are separated.
- The Data Warehouse data are integrated.
- The Data Warehouse contains historical data over a long time horizon.
- The Data Warehouse data are snapshot data captured at a given point in time.
- The Data Warehouse data are subject-oriented.
- The Data Warehouse data are mainly read-only with periodic batch updates from operational data. No online updates are allowed.
- The Data Warehouse development life cycle differs from classical systems development. the Data Warehouse development is data driven; the classical approach is process driven.
- The Data Warehouse contains data with several levels of detail; current detail data, old detail data, lightly summarized, and highly summarized data.
- The Data Warehouse environment is characterized by read-only transactions to very large data sets. The operational environment is characterized by numerous update transactions to a few data entities at the time.
- The Data Warehouse environment has a system that traces data sources, transformations, and storage.
- The Data Warehouse’s metadata are a critical component of this environment. The metadata identify and define all data elements. The metadata provide the source, transformation, integration, storage, usage, relationships, and history of each data element.
- The Data Warehouse contains a charge-back mechanism for resource usage that enforces optimal use of the data by end users.
*The 12 Rules of Data Warehouse for a Client/Server World, Data Management Review, Vol. 4, May 1994.
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