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A database designer should not normalize with impunity, as this may have an effect on speed within the database and the retrieval of data. In good normalization, the removal of the duplication of data will provide faster sorting of data and queries that run faster, thereby improving performance. Although normalization will produce an efficient database, it is possible to overnormalize data by creating too many relationships and too many slim, small tables, so that to retrieve one piece of information requires access to many tables and many joins between these tables. A knowledgeable designer knows when to stop normalizing and does not take things just that stage too far, such as having too many relationships. This knowledge comes with experience and practice mainly, but in our database example you ll learn where to stop.
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Tip When any reference tables return one row of data without further table references to retrieve that
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information, that s a signal to stop normalization.
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In this section of the chapter, we ll model our example in a method known as logical modeling. The purpose of the logical model is to show the data that the application must store to satisfy business requirements. It demonstrates how this data is related and explores any integration requirements with business areas outside the scope of the development project. It is created without any specific computer environment in mind, so no optimization for performance, data storage, and so forth is done. In logical modeling, the term entity is used to mean a conceptual version of a table. As we re still in the logical modeling stage of designing our database, I ll use entity rather than table in this discussion, since it is less tied to implementation. Also within logical modeling, a column of data is referred to as an attribute. To build our logical model, we ll take the information gathered previously in the chapter and implement attributes in our entities. From that, we ll see how we need to alter our design. The question remains, what should be contained in an entity Three principles should govern the contents of an entity: Each entity should have a unique identifier. Only store information that directly relates to that entity. Avoid repeating values or columns. The sections that follow provide more detail about each principle.
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CHAPTER 3 DATABASE DESIGN AND CREATION
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Each Entity Should Have a Unique Identifier
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It must be possible to find a unique row in each entity. You can do this through the use of a unique identifying attribute or the combination of several attributes. However, no matter which method you use, it must be impossible for two rows to contain the same information within the unique identifying attribute(s). Consider the possibility that there is no combination of attributes in an entity that can make a row unique, or perhaps you wish to build a single value from a single attribute. SQL Server has a special data type, called unique identifier, that can do this, but a more common solution is to build a column attribute with an integer data type, and then set this up as an identity column. You ll learn more about this technique when building the tables in 5.
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Only Store Information That Directly Relates to That Entity
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It can be very easy in certain situations to have too much information in one entity and therefore almost change the reason for the existence of the specific entity. Doing so could reduce efficiency in an OLTP system, where duplicate information has to be inserted. It could also lead to confusion when an entity that has been designed for one thing actually contains data for another.
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Avoid Repeating Values or Columns
Having attributes of data where the information is an exact copy of another attribute within either the same entity or a related entity is a waste of space and resources. However, what tends to happen is that you have repeated values or attributes within two or more tables, and therefore the information is duplicated. It is in this scenario that you are expected to avoid the repeating values and move them elsewhere.
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