Database
Database is collection of interrelated data. Database stores data about the entities (objects); entity can be physical or abstract. Data in database is stored in the tabular format; rows of the table represent a record (record of an entity) and columns of the table represent attributes of the entity. Database management system stores data in structured format and allows ease access and modification of the data; includes language to create, access, and manipulate data stored in the database. This language is known as Structured Query Language (SQL).
Database management system (DBMS) is an important component of the Management Information System (MIS). MIS works and processes data and produces information. Data should be in correct format for MIS to process and produce information. There are several advantages of storing data in database over storing data other systems like file system:
MIS needs data, without data information can’t be produced. It is necessary to store data in the organized and well-managed form such that it can be retrieved and processed easily. Organizations take advantage with well managed data; database management system is the best option for storing data in the organized manner.
Here a simple example is given to shown how database management system helps managers in decision making process. Let’s consider a Library which provides books to its members; only members can borrow books from the library. The employees of the library can create membership for the users; they manage all the data of the library; insert/edit information of new books, members, transactions (borrow and return). The employees need several information for smooth operation of the library. The employees have to decide:
By storing information of books, members, transaction (borrows, returns, orders etc.) in database the employees of the library can get answer (information) to above queries easily and effectively. Books, members are entities of the library system and borrows, orders are relationship between the entities.
Three tables are created in the database to store data of books, members and issues. The books table will store data of the books only, member table will store data of the members only and issues will store data about the books borrowed by the members.
Table 1 Books
Table 2 Members
Table 3 Issues
Following SQL statements will produce information which will be of value for the employees in answering above questions:
Table 4 Number of Books Issued by each member
Table 5 Number of books issued
Table 6 Number of different types of books issued
Table 7 Number of male and female members
Table 8 Number of books issued by each gender
Data about only one entity (object) should be stored in a table. It is not a good practice to store data of more than one entity in the single table; storing data of more than one entity in the single table creates different problems. Consider following table in which employee data and book data are stored in the single table to show who has borrowed which book; this table is able to provide information about the borrows made by the members but there are problems:
Table 9 Books Issued by members
Here, the given table shows who borrowed which book and when. In the give table there is repetition of same data; records of Mohan, Sheetal are repeated; similarly books information are also repeated. The repetition of records means more storage requirements. If we want to change address of Mohan, we have to update all the records of Mohan; missing to update one record of Mohan will make data inconsistent. These issues stand up because data of two different entities (member, book) are stored in the single table.
Above images of tables: book, member and issues are given. In those tables, there is no repetition of records; no waste of memory space; and updating member or book data can be done easily; updating address of Mohan in one place is sufficient. That design in which a table storing data of one entity only is preferred over the flat tables containing data of more than one entity
Database helps to make data consistent. Organizations have several rules on data like: age should be greater than 20 or gender must be among three values (male, female, or other) only. These kinds of rules can be easily imposed in the database. These rules are known as integrity constraints. The integrity constraints are specified at the time of designing table.