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Data Warehouse: Bill Inmon’s Vision

Originally published March 23, 2005

In articles written for the Business Intelligence Network, Bill Inmon defines his concept of the data warehouse as follows:

“A Data warehouse needs to service the needs of all of its users, not just one class of user.     In an enterprise environment there are many classes of users:

  • Accounting;
  • Finance;
  • Marketing
  • Production;
  • Service; Etc.  

Each of these user classes is a separate community with its own way of looking at the data in the data warehouse. This requires that the data warehouse have as its basis, relationally designed tables for the data.

The nice thing about relationally designed tables as a basis for a data warehouse is that in a relational format the relational data can be reshaped and reformed into any configuration that is needed.  Stated differently, when relational design is done properly and the data exists at a low level of granularity in the data warehouse, any other configuration of data can be supported – multidimensional cubes, star schemas, flat files, etc.

The paradigm for relational data in the data warehouse is that data should be at a low level of granularity and in third normal form (3NF).

After the data is so shaped, then it is possible to “lightly denormalize” the data if it is commonly used in that manner by all classes of users.”

The Inmon position further holds that once this relational foundation is in place, it has the flexibility to support multidimensional data marts and other data structures, such as, exploration warehouses, data mining data bases, etc.

Bill Inmon espouses an iterative or spiral approach to the development of a large data warehouse.

“The relational foundation for the data warehouse needs to be built iteratively, one table at a time. Under no circumstances is it optimal to build a data warehouse all at once, using the “big bang” approach.  Accordingly, the methodology that is appropriate to the building of a data warehouse is known as the “spiral approach”…. In the [iterative] spiral approach one small part of the system is…complet[ed]…Small parts of the relational data warehouse are added with each new iteration.”

In the Inmon model, by using the iterative method, errors and adjustments can be applied to a small amount of data or code, without the need to re-program or code large amounts of data in the data warehouse...

This relationally designed or 3NF approach permits a granularity of integrated data which provides maximum flexibility to the enterprise. If the enterprise has new requirements for the data that is warehoused, the data in the data warehouse is in a form that is ready to be shaped or formatted to meet the new requirements.

Bill Inmon has provided an excellent description of his concept of data warehouse design:” Data warehouses are arranged [by] the corporate subject areas…in the corporate data model. Usually, the data warehouse is built and owned by centrally coordinated organizations. … [It] is a truly corporate [-wide] effort.”

He also advises that the data warehouse contains the corporation’s most granular level of data. The structure and content of the data warehouse is not dictated by the requirements of any one department, but instead is intended to serve the entire corporation’s data requirements.

The data warehouse, therefore, requires scalable technology to properly house it, because of the tremendous volume of data needed for the entire enterprise.  The data warehouse also contains historical data from many legacy sources.

A critical design tenet of a data warehouse is that it is NOT a collection of data marts but is, in fact, a physically distinct component altogether.

The next article will focus on specific similarities and differences between the Inmon Corporate Information Factory and the Kimball Bus Architecture.

  • Katherine Drewek

    Katherine (1950-2010) had more than 30 years of experience in the editorial and corporate law environment. She was responsible for the content review, editing and formatting of international newsletters focusing on business intelligence and data warehousing. She was a frequent lecturer and panelist for the American Bar Association, the National Association of Credit Managers and the Corporate Practice Institute. She had been a mentor for the Women's Leadership Conference and served as Managing Editor for BeyeNetwork.

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