What is DBMS | Advantages and Disadvantages of DBMS ?

INTRODUCTION TO DBMS:-

DBMS stands for Database management system. As the name suggests, the database management system consists of two parts. They are:-

Database
Management System

1. Database:- To find out what database is, we have to start from data, which is the basic building block of any database management system.

Data:- It is a raw set of facts and figures associated with an individual, an entity, or an event. It is basically a collection of unorganized facts or concepts that does not any meaning. Data can be convey represented in various forms i.e. in symbols, figures, characters, pictures, audio, video etc. (e.g. 1, ANSH, 19 etc).
Record:- A record can be defined as a collection of related data items, e.g. in the above example the three data items (1, ANSH, 19) had no meaning. But if we organize them differer In in the following way, then they collectively represent meaningful information or a record.

Table or Relation:-

Collection of related records. The columns of this relation / table 19 are called Fields, Attributes or Domains. The rows are called Tuples or Records.

Database:-
Collection of related relations or tables. Consider the following collection ot tables:

We now have a collection of 4 tables. They can be called a "related collection" because we can clearly find out that there are some common attributes existing in a selected pair of y together to find out the complete details ofa student. Questions like "Which hostel does the youngest student live in?" can be answered now, although Age and Hostel attributes are in an tables. Because of these common attributes we may combine the data of two or more tables ,

In a database, data is organized strictly in row and column format. The rows are called Tuple or Record. The data items within one row may belong to different data types. On the other hand, the columns are often called Domain or Attribute. All the data items within a single attribute are of the same data type.

2. Management System:- A management system is a set of rules and procedures which help us to create organize and manpulate the database. ll also helps us to add, modify delete data items in the databasa The managcment system can be cither manual or compulerizcd.

The manpement system is important because without the existence of some kind of rula. hd regulialions it is not possible to maintain the datahase. We have to select the particul ltributes which should be included in a particular table: the common attrputcs to create Coship betwecn two tables: if a new record has to he inserted or deleted then whick bes shOuld have to be handled cte. Thesc issuCs must be resolved by having some Kind of rules to follow in order to maintain the integrity of the database.

ADVANTAGES OF DBMS :-

Minimized redundancy: The data in a DBMS is more concise because, as a general rule. the information in it appears just once. This reduces data redundancy, because redundaney is the problem of storing the same data item in more than one place. 1.10.2 DIS Redundancy creates several problems like requiring extra storage space, entering same data more than once during data insertion, and deleting data from more than one place during deletion. Minimizing redundancy can therefore significantly reduce the cost of storing information on hard drives and other storage devices and wastage of time in entering data again and again.
Elimination of Incorisistency: In the file processing system information is duplicated throughout the system. So changes made in one file may be necessary be carried over to another file. This may lead to inconsistent data. So we need to remove this duplication of data in multiple file to eliminate inconsistency. DBMS centralize the entire database so that particulars changes once made are reflected to all the tables where a ficld is stored.
Sharing of Data: In a paper-based record keeping, data cannot be shared among many users. But in computerized DBMS, many users can share the same database if they are connected through a network.
Data security: We can restriet kind certain people from accessing the database or allow them to see certain portion of the database while blocking sensitive information. This is not possible very easily in a paper-based record keeping.
Flexibility of the System is Improved: Since changes are often necessary to the contents of the data stored in any system, these changes are made more easily in a data; rath centralized database than in a conventional system. Applications programs need not to be changed on changing the data in the database.
Standards can be enforced: Since all access to the database must be through DBMS, so standards are easier to enforce. Standards may relate to the naming of data, format of data. structure of the data etc. Standardizing stored data formats is usually desirable for the purpose of data interchange or migration between systems
Data Integrity: Accurate, consistent, and up-to-date data is a sign of data integrity. DBMS supports data integrity. Data integrity means that the data contained in the database is both accurate and consistent. Therefore, data values being entered for storage could be checked to ensure that they fall within a specified range and are of the correct format. Moreover updates and changes to the data only have to be made in one place. The chances of making a mistake are higher if you are required to change the same data in several different places than if you only have to make the change in one place .
Provides Backup and Recovery: Centralizing a database provides the schemes such as recovery and backups from the failures including disk crash, power failures, software errors which may help the database to recover from the inconsistent state to the state that existed prior to the occurrence of the failure, though methods are very complex .

DISADVANTAGES OF DBMS :-

High Cost: A significant disadvantage of the DBMS system is cost. As DBMS needs computers, we have to invest a good amount in acquirimg the hardware, software, installations factilitis and training of user .
Complexity of Backup and Recovery: While centralization reduces duplication, the lack of duplication requires that the database be adequately backed up so that in the case of failure the data can be recovered. Backup and recovery operations are fairly complex in a DBMS environment. We have to keep regular backups because a failure can occur any time. Taking backup is a lengthy process and the computer system cannot perform any other job at this time .
Security Threats: Even with safeguards in place, it may be possible for some unauthorized users to access the database. So, security system must be very robust. If sOmeone can bypass the security system then the database would become open to any kind of mishandling.

DATA MODELING FOR A DATABASE :-

Data modeling is a way to structure and organize data so it can be used easily by dases. Unstructured data can be found in word processing documents, email messages, processing by a database. So in a way, data modeling is concerned with how the data looks .

Data modeling is routinely used in conjunct with a database management system, Dat INTRODUCTION it has been modeled and made ready for this svstem can be identified in various ways, sle as ccording to what they represent or how thev relate to other data. "The idea is to make da P Dle as possible, so analysis and integration can be done wIth as nnue ettort a necessary.

Conceptual Data Modeling - It identifies the highest-level relationships between different entities .
Enterprise Data Modeling - Enterprise data modeling is similar to conceptual dat modeling. but addresses the unique requirements of a specific business.
Logical Data Modeling This data modeling illustrates the specific entities, attribute and relationships involved in a business function. It serves as the basis for the creation of th physical data model.
Physical Data Modeling- It represents an application and database-speciti implementation of a logical data model.

DATA INTEGRATION:-

Data integration combines data from multiple sources into a single data store, such as motho data warehouse. These sources may include multiple databases, data cubes, or flat files.

Why Data Integration is required?

Often large companies and enterprises maintain separate departmental databases to store the data pertaining to the specific department. Although such separations of the data provide them beter manageability and security, performing any cross departmental analysis on these .

For exanmple, if marketing department and sales department maintain two secluded databases, then it might not be possible to analyze the effect of a certain advertising campaign hy the marketing department on sales of a product. Similarly, if HR department and production department maintain their individual databases, it might not be possible to analyze he correlation between yearly incentives and employec's productivity .

Data integration provides a mechanism to integrate these data from different departments into a single database schema.

DATA ABSTRACTION :-
The major purpose of a database system is to provide users with an abstract view of the system. The system hides certain complex details from the user like- how data is stored and shows only those database records to the user which he/she demands. This is called Data sal dat abstraction.

In DBMS, the database can have different aspects to reveal if seen from different levels of abstraction. The term abstraction means the amount of detail you want to hide. Any entity can be seen from different perspectives and levels of complexity to make it a reveal its tribute of the pecific current amount of abstraction. Let us illustrate by a simple example:

A computer reveals the minimum of its internal details, when seen from outside. We do not know what parts it is built with. This is the highest level of abstraction, meaning very few details are visible. If we open the computer case and look inside at the hard disk, motherboard, CD drive, CPU and RAM, we are in middle level of abstraction. If we move on to open the hard disc and examine its tracks, sectors and read-write heads, we are at the lowest level of abstraction, where no details are invisible.

In the same manner, the database can also be viewed from different levels of abstraction to reveal different levels of details. From a bottom-up manner, we may find that there are three levels of abstraction or views in the database:

External or User view: In this database view, maximum detail about the database wille hidden from the user. In this view, only the restricted portion of the database is available to end users. It implements highest level of data abstraction .
Conceptual or Logical view: This view will provide some more detail about the database to the user like- structure or schema detail of the database. It implements middle level of data abstraction.
Internal view: This view will provide internal or storage detail about the database. It implements lowest level of data abstraction .