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The Term Relational Database - Coursework Example

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From the paper "The Term Relational Database" it is clear that flexible retrieval technique greatly aids database administrators (DBAs) in testing and verifying the integrity and content of databases. SQL’s features serve to make it one of the best languages in terms of user-friendliness…
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The Term Relational Database
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Relational Database A relational database is one that uses tables (with rows and columns) to present information. In the context of relational databases, tables are referred to as “relational” because they are a collection of identical objects (rows). Data in a table can be related in terms of common concepts or keys, and the ability to retrieve related information from a table is the genesis of the term relational database (Pathak, 2008). In the case of a relational database, an RDBMS (relational database management system executes data storage, maintenance, and retrieval, just like a typical database should. Integrity Rules Relational databases use specific integrity rules to facilitate accurate collection of data and to make that data accessible. Firstly, the rows in a relational database must all be unique. In case of duplicate rows problems can crop up when resolving which of the two likely selections is the right one. For most DBMSs (databases management systems) users are able to specify that duplicate rows are not permitted, and when that is done the DBMS will block the addition of any rows that are identical to an existing one. Another integrity rule of relational databases is that column values should not be repeating arrays or groups. The third involves the logic of a null value. A database handles situations where information may not be available by employing a null value to show that a value is absent (Pathak, 2008). It is not equal to a blank or zero; a blank is equal to another blank and a zero is only equal to another zero. Two null values are not equal. When each row in a table is unique, it is possible to use one or more columns to mark a specific row. This distinct column or group of columns is referred to as a primary key. Any column that forms a primary key cannot be null; in any case it were the primary key which it is a part of would cease to be a complete identifier. This rule is known as entity integrity. Importance Relational databases can greatly enhance the quality control and accessibility to organizations’ sensitive and valuable information materials. It can contribute towards a competitive edge by facilitating business analysis that can help to determine methods of improving products and services (Pathak, 2008). In comparison to non-relational database settings, relational databases are more flexible hence easily adapt to dynamic business needs. In addition, unlimited access to sensitive data means better data for more effective decision-making. Relational databases can also have a huge positive impact on numerous MIS development settings by minimizing the application backlog and reducing the time and cost needed to design applications. The flexibility and ease of change aspect also inspires a significant reduction in the overall amount of maintenance of applications. In summary, relational databases can enhance the effectiveness and productivity of MIS professionals, which results in greater user satisfaction and confidence (Pathak, 2008). Opting for relational databases can position organizations to fully exploit future technological advances. Normalization Normalization is the process of minimizing data redundancies in databases, and is often employed when designing and redesigning databases (Whitehorn & Marklyn, 2001). This includes the creation of tables and the establishment of relationships between those tables. This is based on rules developed to not only protect the data but also to make the database more flexible by reducing redundancy and inconsistent dependency (Whitehorn & Marklyn, 2001). It is an important procedure that if understood and well implemented, can significantly improve one’s understanding of SQL. Importance It highlights dependency and problems in data and hence facilitates understanding of the nature of data. Regulates/minimizes data redundancy, hence minimizing storage requirements and frequency of standard maintenance. Enables the creation of distinct identification codes for records in a database. Each normalization stage often eliminates a specific type of unwanted dependency. Facilitates simple retrieval of data in response to queries and reports (Whitehorn & Marklyn, 2001). The third normalization form (3NF) results in well-designed databases that offer a higher level of independency. Helps define efficient data structures Normalized data structures are very useful in the design of files and databases Eliminates unwanted dependency relationships in database files. Logical and Physical Database Design Logical This design deals with collecting business requirements and converting them into a model. It usually encompasses the needs of the organization, not the database, although the organizational needs are used in determining the needs of the database (Stephens & Plew, 2001). Logical design constitutes collecting information about business processes, organizational units, and categories of data (business entities). Deliverables of logical database design often include: User feedback information Entity relationship diagrams Business process diagrams Physical Involves the actual (physical) design of a database based on the needs determined during logical modelling (Stephens & Plew, 2001). Logical modeling mainly entails collecting organizational requirements, with the latter stages focused on the goals and requirements of the database. Physical modeling, on the other hand, deals with the conversion of the logical design into an RDBMS (Stephens & Plew, 2001). Physical modeling involves defining objects at the schema level. Deliverables of physical database design often include: Server model diagrams (which display tables, columns, and relationships within a database). User feedback documentation Database design documentation SQL SQL is often cited as the best and most commercially marketed query language today. One of the reasons it is so popular is because of its ease of usability because of its simple rules/structure. From users’ perspectives, SQL allows them to choose what should be done instead of the more sophisticated procedural task of choosing how to execute a task (Elmasri & Navathe, 2000). The language also offers a small and intuitive package of command statements that significantly enhance its power and flexibility, making it even more user-friendly (Rob & Coronel, 2007). In terms of usability and user friendliness, SQL is considered to be the best because it allows users to retrieve information and develop meaningful information with little hassle (Elmasri & Navathe, 2000). It is worth noting that this flexible retrieval technique greatly aids database administrators (DBAs) in testing and verifying the integrity and content of databases (Rob & Coronel, 2007). In summary, SQL’s features serve to make it one of the best languages in terms of user friendliness, and the reasons provided here go a long way in vindicating this statement. References Elmasri, R., & Navathe, S. (2000). Fundamentals of database systems (3rd Ed.). Reading, Mass.: Addison-Wesley. Pathak, N. (2008). Database management system. Mumbai [India: Himalaya Pub. House. Rob, P., & Coronel, C. (2002). Database systems: design, implementation, and management (5th Ed.). Boston, MA: Course Technology. Stephens, R. K., & Plew, R. R. (2001). Database design. Indianapolis, Ind.: Sams. Whitehorn, M., & Marklyn, B. (2001). Inside relational databases (2nd Ed.). London: Springer. Read More
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