Importance of Relational Databases

The term database implies an organized and logical collection of data in digital form. It is a centralized pool of data stored to achieve certain objective of an organization. A database is composed of two parts: intentional part and extensional part. The intentional part is a set of definitions which describe the structure of the database. This part is implemented using data definition language (DDL) and it is static. On the other hand, the extensional part is the total set of data within the same database. Database Management Systems (DBMS) are used for quality management of data. A database management system is a software system that uses standard method of cataloging, retrieving and running queries on data. It manages incoming data, organize it and later provide ways for which to modify the data. Such systems include: Oracle, IBM, Microsoft access, MySQL and SQLite (Raju, 2010).

Databases have various advantages within organizations. For instance, Database management systems are used to control data redundancy. Redundancy is the amount of wasted space in the course of data storage. The data approach does not entirely eliminate redundancy but control only the amount of redundancy within the aforementioned database. Database management systems also ensure data consistency. The risk of inconsistency is reduced by ensuring that the records of the organization are safe and in order. Some inconveniences are eliminated. Sharing of data is also enhanced among the organization’s management and staff. Instead of employing office messengers, database management systems are thus used for data sharing. There is improved data integrity. Database integrity is the validity and consistency of data stored in a database. Integrity is stored in terms of constraints which may include the primary key, foreign key, NOT NULL, UNIQUE, CHECK among others. As a result, stored data looks more presentable. Security of stored data is also improved. Data is protected from unauthorized users. This is achieved through the use of usernames, passwords and accessed privileges, which is mainly the work of the database administrator. Also, through data independence, there is improved maintenance. As a result, the schema definition in one level can be modified without affecting the schema definition in the subsequent level (Codd, 1970).

Relational database refers to a kind of database conforming to the theory of relational model. The software used is called relational database management system (RDBMS).

The concepts used to describe a relational database system are as follows. In this model, data is presented as a collection of relations. These relations are depicted as tables. Tables are created within relational database management systems through specific databases which are created in forms of rows and columns at large. These tables have columns which are attributed to various entities, modeled by the created table. For example, in an employee table, there is usually the following variable, which is, name, address, employee among others. The tables have rows which represent a single entity. Tables have sets of attributes which are usually perceived to be unique ‘keys’, uniquely identifying those entities.

The rules used to ensure database integrity ensure that the data remain accurate and is accessible whenever needed. The first rule in creating relational table states that the rows within the tables should be distinct and unique in nature. Duplicate rows will result to problems in selecting the right tables to be created altogether. The user can specify the model of the relational database, by not allowing duplicate rows. Secondly, the column values are made sure that they do not repeat themselves as groups or arrays. The third aspect involves the null value so that when the data is not available, a null value is used to indicate a missing value. Data stored in relational database is accessible through relations. It is worth noting that database management systems have reduced the human effort of manually recording and analyzing data.