Data Modeling Theory

Normalization And Modeling Theory

Let’s begin by briefly reviewing data modeling theory from a normalization perspective. It is interesting to note that Dr. Codd coined the term normalization in reference to current events of the day. At the time Dr. Codd was developing his mathematical rules for data redundancy, President Nixon was normalizing relations with China. Because Nixon was normalizing relations, Dr. Codd decided that he would also normalize relations as he refined his rules. (I’m not making this up!)

For database systems, a systems developer begins by taking raw, de-normalized relations from a systems analysis. Then, the developer takes the relations to third normal form and looks at the introduction of redundancy for improved performance. Of course, data redundancy becomes even more important for an Oracle warehouse developer than for a traditional OLTP designer, so we will carefully explore the options of table de-normalization in this chapter. In addition, we will also design a method for storing the pre-calculated data summaries that were defined in our systems analysis. Finally, as pointed out in the last chapter, we cannot always predict all the possible combinations of data attributes that will compose aggregate fact tables, so we must design a method for allowing our end users to dynamically define aggregation criteria and store the aggregate values into Oracle tables.

This text does not attempt to fully explore data normalization because dozens of texts are available for that purpose. Instead, this text offers a brief discussion of the normalization process as it applies to our example from Guttbaum’s Grocery. The processes of normalization was originally intended to be a method for decomposing data structures into their smallest components. The process begins with the original data structures which are called un-normalized relations, and progresses through first normal for to third normal form. At this stage the data structures are completely free of redundancy and are at their most decomposed level. To fully appreciate the process, let’s take a look at the successive process of normalization.

This is an excerpt from "High Performance Data Warehousing", copyright 1997.

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