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:

  1. The Data Warehouse and operational environments are separated.
  2. The Data Warehouse data are integrated.
  3. The Data Warehouse contains historical data over a long time horizon.
  4. The Data Warehouse data are snapshot data captured at a given point in time.
  5. The Data Warehouse data are subject-oriented.
  6. The Data Warehouse data are mainly read-only with periodic batch updates from operational data. No online updates are allowed.
  7. The Data Warehouse development life cycle differs from classical systems development. the Data Warehouse development is data driven; the classical approach is process driven.
  8. The Data Warehouse contains data with several levels of detail; current detail data, old detail data, lightly summarized, and highly summarized data.
  9. 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.
  10. The Data Warehouse environment has a system that traces data sources, transformations, and storage.
  11. 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.
  12. 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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