barcode addin for excel 2007 E-R Model and Normalization in Software

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7101 E-R Model and Normalization
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When we carefully de ne an E-R diagram, identifying all entities correctly, the tables generated from the E-R diagram should not need further normalization However, there can be functional dependencies between attributes of an entity For instance, suppose an employee entity had attributes department-number and department-address, and there is a functional dependency department-number department-address We would then need to normalize the relation generated from employee Most examples of such dependencies arise out of poor E-R diagram design In the above example, if we did the E-R diagram correctly, we would have created a department entity with attribute department-address and a relationship between employee and department Similarly, a relationship involving more than two entities may not be in a desirable normal form Since most relationships are binary, such cases are relatively rare (In fact, some E-R diagram variants actually make it dif cult or impossible to specify nonbinary relations) Functional dependencies can help us detect poor E-R design If the generated relations are not in desired normal form, the problem can be xed in the E-R diagram That is, normalization can be done formally as part of data modeling Alternatively, normalization can be left to the designer s intuition during E-R modeling, and can be done formally on the relations generated from the E-R model
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7102 The Universal Relation Approach
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The second approach to database design is to start with a single relation schema containing all attributes of interest, and decompose it One of our goals in choosing a decomposition was that it be a lossless-join decomposition To consider losslessness, we assumed that it is valid to talk about the join of all the relations of the decomposed database Consider the database of Figure 720, showing a decomposition of the loan-info relation The gure depicts a situation in which we have not yet determined the amount of loan L-58, but wish to record the remainder of the data on the loan If we compute the natural join of these relations, we discover that all tuples referring to loan L-58 disappear In other words, there is no loan-info relation corresponding to the relations of Figure 720 Tuples that disappear when we compute the join are dangling tuples (see Section 621) Formally, let r1 (R1 ), r2 (R2 ), , rn (Rn ) be a set of relations A
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II Relational Databases
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7 Relational Database Design
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branch-name Round Hill loan-number
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loan-number L-58 amount
loan-number L-58 Figure 720
customer-name Johnson
Decomposition of loan-info
tuple t of relation ri is a dangling tuple if t is not in the relation Ri (r1
rn )
Dangling tuples may occur in practical database applications They represent incomplete information, as they do in our example, where we wish to store data about a loan that is still in the process of being negotiated The relation r1 1 r2 1 1 rn is called a universal relation, since it involves all the attributes in the universe de ned by R1 R2 Rn The only way that we can write a universal relation for the example of Figure 720 is to include null values in the universal relation We saw in 3 that null values present several dif culties Because of them, it may be better to view the relations of the decomposed design as representing the database, rather than as the universal relation whose schema we decomposed during the normalization process (The bibliographical notes discuss research on null values and universal relations) Note that we cannot enter all incomplete information into the database of Figure 720 without resorting to null values For example, we cannot enter a loan number unless we know at least one of the following: The customer name The branch name The amount of the loan Thus, a particular decomposition de nes a restricted form of incomplete information that is acceptable in our database The normal forms that we have de ned generate good database designs from the point of view of representation of incomplete information Returning again to the example of Figure 720, we would not want to allow storage of the following fact: There is a loan (whose number is unknown) to Jones in the amount of $100 This is because loan-number customer-name amount and therefore the only way that we can relate customer-name and amount is through loan-number If we do not know the loan number, we cannot distinguish this loan from other loans with unknown numbers
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