Logical Design Part 2
August 30, 2013
Hello sirs, my name is , it has come to my attention that there are some misconceptions about the value in normalizing your database. I wanted to write this correspondence to address any concerns that you may have about flexibility while entering your data into the system. This letter is to assure you and the other members of your executive board that you will have some flexibility within your E-R Model. I would like to introduce you to the concept of normalization. Normalization is used to control or reduce the amount of data redundancy and help avoid inconsistent data in your E-R Model. There are some benefits to normalization one of them is the prevention of modification anomalies in the data. Anomalies can lead to the loss of critical data in your E-R Model; normalization will help organize your data, which will prevent redundancy in your E-R Model. Normalization also maintains and establishes the integrity of your data tables and should eliminate inconsistencies in your data dependencies. As with almost everything in business and life there are some pros and cons for normalization. One pro to normalization is that a well-normalized database is faster at accessing and writing data to your E-R Model. The normalization causes relational inconsistencies and this means that there would be no redundancy in your Model. Another pro is also related to performance, a fully normalized expression of a data model is compacted data in terms of the bytes per unit of information, and this would help with performance as well. Some of the cons are that normalization requires some discipline in keeping your data well indexed. Normalization also requires skill in providing functional views of your data so that consumers can comprehend the OLTP applications, and this can be expensive. I mentioned data redundancy and I would like to explain what it is. Data redundancy happens in a DBMS that has fields, which are repeated...
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