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1. Discuss attribute semantics as an informal measure of goodness for a rela - tion schema.

2. Discuss insertion, deletion, and modification anomalies. Why are they considered bad? Illustrate with examples.

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  1. Today, 00:41
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    1. The attribute semantics as an informal measure of goodness for a relation schema can be of two types, (i) Logical (or conceptual) level-It tells about how the users interpret the relation schemas and the meaning of their attributes. (ii) Implementation (or storage) level-It tells about how tuples and their values are stored in storage.

    2. Insertion anomalies means inserting a new attribute in the existing database, deletion means deleting any particular attribute and modification means modifying the data, these are considered bad because, when this process applies to any database we have to select the correct path and location of data otherwise it will not work correctly, and make a copied file.
  2. Today, 02:54
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    When attributes are intertwined together they form a relationship, it is believed that attributes that have one to one relation have a proper interpretation and better meaning which are assumed to be associated by them.

    Tables that does not have a complete data may encounter problems called update anomalies, which have different categories like insertion, deletion, or modification anomalies

    Explanation:

    When attributes are intertwined together they form a relationship, it is believed that attributes that have one to one relation have a proper interpretation and better meaning which are assumed to be associated by them. The semantics of a relation is defined as the the exposition of value attribute in a tuple. That is to say a better way of the explanation of a relations attributes is a measure of informal well known relation designed.

    Tables that does not have a complete data may encounter problems called update anomalies, which have different categories like insertion, deletion, or modification anomalies. For example of a table with on useful data data called EMP-Department. There are two categories of insertion anomalies, For this method to be useful for the detail of a new employee in Emp-Department, we must add either value attribute for the department that the employee is engaged in or void. For the second method, an the attribute value must be entered for the department 2 well so that there will be a consistent value for department number 5 in other field in EMP-Department. When a department does not have a new employee It is difficult to insert the department value
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