Conversation to First Normal Form (1NF)
Step two: Identification of the Primary Key
For maintenance of primary key, it is important to identify uniquely attributed value
Step Three: Identifying all Dependencies
Dependency diagrams can be significant obtaining a ‘bird's-eyesight’ of all the relations involved in the tables attribute, and their implication makes it less likely for an overlook of important decencies
Converting to Second Normal Form (2NF)
The relational database when designed has the possibility of being easily improved through conversion of the database to a format identified as the 2NF (Chapple, 2011). To ensure the effectiveness of the 2NF format, it is important first to ensure elimination of all partial dependencies forms the 1NF format.
Step Two: Identifying the Dependent Attributes
Determining all the dependent attributes among other attributes
Partial dependency can be realized primary key of table’s entails several attributes; a table that has a primary key with a single attribute can be considered 2NF in case it is in 1NF.
Converting to Third Normal Form (3NF)
For all the transitive dependencies, considering its determinant as PK is important for a new table.
Step Two: Identifying the Dependent Attributes
Coming up with attributes that tend to dependent on one another as identified in Step one and identifying the dependencies
Step Three: Eliminating the Dependent Attributes from Transitive Dependency
Eradicating the dependency attributes within the transitive relationship from the tables
Drawing a dependency diagram that assists in showing all the tables defined in steps
Checking the tables as well as the modified tables in the third step to ensure that all the tables have determinant and notable has inappropriate, partial or transitive dependency
Example:
An example relevant to a college environment that provides a reason for conversion of database tables would have a database table that has student class information, identification, and profession data (Mitrovic, 2002). Converting database tables have relevance with college environments due to the ease of generating efficiently information; normalization will be significant in reflecting life structure of database systems that would be useful at the University
Denormalization for performance
Once the database is created in normalization forms, it is important to consider benchmarking and deciding to back off from normalization with an aim of improving performance for particular applications. However, denormalization tends to be based on advanced knowledge, and it should be carried out only in cases where performance issues are necessary (Bahmani & Bahmani, 2008).
An example of denormalization information on database table would be a rational diagram that involves a Consumer and an Agent, which provides the connection between the consumer and their agent which involves the attributes that have information regarding the Agent and for the attributes of the Consumer including basic information and the information that the company has on them. Redundant data can be storing Zip Codes, and City eradicating can be done through programming the validation of city based on zipping code
Business Impact
Business rules impact both normalizations as well as denormalization by puzzling the idea behind other terms that are applied to the database in case the business rules written in both types of tables that needs to be ensured are not written in an elevated language doing that to ensuring it is hard for other people to conceptualize (Westland, 1992). When forming business rules in a denormalized table, there has to be assurance of test and defined rules.
References
Chapple, M. (2011). Database normalization basics.
Mitrovic, A. (2002, December). NORMIT: A web-enabled tutor for database normalization. In Computers in Education, 2002. Proceedings. International Conference on (pp. 1276-1280). IEEE.
Bahmani, A. H., Naghibzadeh, M., & Bahmani, B. (2008, May). Automatic database normalization and primary key generation. In Electrical and Computer Engineering, 2008. CCECE 2008. Canadian Conference on (pp. 000011-000016). IEEE.
Westland, J. C. (1992). Economic incentives for database normalization.Information processing & management, 28(5), 647-662.
