Data modeling techniques for data mining IBM by Chuck Ballard, Dirk Herreman, Don Schau, Rhonda
By Chuck Ballard, Dirk Herreman, Don Schau, Rhonda Bell,
Eunsaeng Kim, Ann Valencic
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2 Bottom Up Implementation A bottom up implementation involves the planning and designing of data marts without waiting for a more global infrastructure to be put in place. This does not mean that a more global infrastructure will not be developed; it will be built incrementally as initial data mart implementations expand. This approach is more widely accepted today than the top down approach because immediate results from the data marts can be realized and used as justification for expanding to a more global implementation.
Derived data is traditionally used for data analysis and decision making. Data analysts seldom need large volumes of detailed data; rather they need summaries that are much easier for manipulation and use. Manipulating large volumes of atomic data can also require tremendous processing resources. Considering the requirements for improved query processing capability, an efficient approach is to precalculate derived data elements and summarize the detailed data to better meet user requirements. Efficiently processing large volumes of data in an appropriate amount of time is one of the most important issues to resolve.
From them we can select the key that is most commonly used to identify the entity. It is called the primary key . Chapter 6. Data Modeling for a Data Warehouse 37 Figure 12. A Sample ER Model. Entity, relationship, and attributes in an ER diagram. 2 Relationship A relationship is represented with lines drawn between entities. It depicts the structural interaction and association among the entities in a model. A relationship is designated grammatically by a verb, such as owns, belongs , and has .