Copyright © 1997 Essential Strategies, Inc.

From a Relational to a Multi-dimensional Data Base

David C. Hay

Figure 4 shows the model of our data mart, based on these assertions. Note that the entity names have been prefaced by "DW" to distinguish them from conceptual model entities. Dw salary contains the attributes not only of the original salary, but also of position assignment, employment, and person. When implemented as a table, it will also acquire the foreign keys to dw month, dw department, dw state, and dw position. Dw department has its attributes as an organization, plus those for its parent company. Dw state, similarly, has acquired the attributes of its parent country.

Figure 4: The Multi-dimensional Data Model

Note also that one dimension of the original model - person - has been eliminated. This means that dw salary occurrences are summarized, adding together the salaries of all people in each combination of position, department, state and month.

Contrary to what many believe, the multi-dimensional model does not replace the conceptual, relational model. Indeed, the development of a normalized conceptual model will be critical to the success of any data warehouse project. It is impossible to manage a set of data marts without one.
Instead, the development of multi-dimensional modeling techniques can be considered an extension to our data management tool kit. When you are developing the databases to be used for specific sets of retrievals, design them according to the userís perspective. That perspective will be constrained and concrete. It also will change over time.
The existence of a stable conceptual model will provide a basis for developing that constrained model ĺ and will make it possible to react to those changes.