A relational models theory asserts that people make use of four elementary models to generate, interpret, consent, coordinate, plan, evaluate and think about aspects of social interactions in all societies. This paper analyses the use of relational data solutions to solve a problem emerging because of data redundancy.
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Data redundancy refers to a data organization issue that allows unnecessary duplication of data within a Microsoft access database. This problem has affected our company, and it requires that a relational data solution employed to make improvements.
In the financial department of the company, a data redundancy problem has arisen making it difficult for financial managers to perform data processing. Data processing involves performing specific operations on a database that entails an organized collection of facts. The financial managers need to make a specific record of each employee, so that they can process their salaries. This problem results from data redundancy. This means that the management of the company cannot exert control over data meaning that the management cannot derive value from data because the data processing tools are redundant (Hernich, 2010).
This problem requires the company to use relational theory that offers relational data solutions to this type of data redundancy. The change needed for the redundant data requires that we make modifications in multiple fields of a single database. This process requires a lot of time and commitment because the behavior exhibited by a flat file database design spreadsheets can defeat the purpose of relational database designs. However, the method offers the most reliable solution.
Therefore, when using relational data solutions to eliminate data redundancy, in the financial department of the company, it requires that one take special care to organize the data in data tables. The normalization method of data arrangement will come into effect. Normalization organizes data to avert data redundancy. It establishes and maintains the integrity of data tables and eliminates inconsistent data dependencies. For example, the financial managers in the company can use normalization to ensure that the data on employee records does not become redundant.
It ensures that one arranges employee data records on separate tables that prevent data redundancy from happening. Normalization requires that people adhere to rules, developed by the database community and ensure efficient data storage. This means that the company will benefit from relational data solutions, in that managers must follow the set rules that the database community has set. This means that employment malpractice will not happen easily (Hernich, 2010).
Normal form rules that normalization use number from one to three for most applications, when using relational data solutions. These rules will help the company achieve a systematic way of entering data on a database because the rules of the third normal form include the rules of the first and the third includes the rules of the second normal form. Therefore, careless mistakes will not happen while entering data on databases because; those responsible must follow the procedure set by the rules.
The first rule requires that one avoid storing similar data in multiple table fields. It requires that each set of related data centers on a separate table and form a primary key. The second rule requires that records become dependent only on a primary key of a table. This creates a separate table for value sets applying to multiple records. The third rule requires that record fields become part of the record key. This eliminates fields that do not depend on the key.
From the above, relational data solutions form the best and easy way of dealing with data redundancy problems. It makes sure that such a problem will not occur again.
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