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Chapter 7.3: Data Modeling for the Structured Environment



               Fig. 7.3.9 The sequence of the steps in doing database design.



           Generic Data Models



           It has been noticed that when a data model is created, it oftentimes applies very nicely to
           other companies in the same industry. For example, a bank—ABC—creates a data
           model. Then one day, it is discovered that the data model for bank ABC is very similar to
           the data model for bank BCD, CDE, and DEF.


           Because of the great similarity of data models within the same industry, there are models
           called “generic data models.” The idea behind a generic data model is that it is much less
           expensive and much faster to acquire a generic data model than it is to build a data model
           from scratch. It is true that any generic data model is going to need customization. But

           even with customization, using a generic data model is much preferable to having to build
           the data model by itself.


           Operational Data Models/Data Warehouse Data Models



           There are different types of data models. There are operational data models and data
           warehouse data models. An operational data model is one that models the day-to-day

           operations of the company. The data warehouse data model is one that is based on the
           informational needs of the organization. The operational data model includes some
           information that is needed for operational processing only, such as a specific telephone
           number. The data warehouse data model does not contain data that are specific to
           operational processing. The data warehouse data model does not contain any summarized
           data. The data warehouse data model does contain a time stamp for every record in the
           model.



















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