Overview on DBMS


Overview on DBMS

Oracle is a relational database management system, which Organizes data in the form of tables. Oracle is one of many database servers based on RDBMS model, which manages a seer of data that attends three specific things-data structures, data integrity and data manipulation. With oracle cooperative server technology we can realize the benefits of open, relational systems for all the applications. Oracle makes efficient use of all systems resources, on all hardware architecture; to deliver unmatched performance, price performance and scalability

Components In DBMS?

A database management system has three components:

A data definition language (DDL) is the formal language programmers use to specify the structure of the content of the database. DDL defines each data element as it appears in the database before that data element is translated into the forms required by application programs. With this help a data scheme can be defined and also changed later.

A data manipulation language (DML) is a language for the descriptions of the operations with data like store, search, read, change, etc. the so-called data manipulation, is needed. Typical DML operations (with their respective keywords in the structured query language SQL):

Add data (INSERT)
Change data (UPDATE)
Delete data (DELETE)
Query data (SELECT)

Data Dictionary: This is an automated or manual file that stores definitions of data elements and data characteristics, such as usage, physical representation, ownership (who in the organization is responsible for maintaining the data), authorization, and security.

Importance of DBMS
A database management system is important because it manages data efficiently and allows users to perform multiple tasks with ease. A database management system stores, organizes and manages a large amount of information within a single software application. Use of this system increases efficiency of business operations and reduces overall costs.

Database management systems are important to businesses and organizations because they provide a highly efficient method for handling multiple types of data. Some of the data that are easily managed with this type of system include: employee records, student information, payroll, accounting, project management, inventory and library books. These systems are built to be extremely versatile.
Without database management, tasks have to be done manually and take more time. Data can be categorized and structured to suit the needs of the company or organization. Data is entered into the system and accessed on a routine basis by assigned users. Each user may have an assigned password to gain access to their part of the system. Multiple users can use the system at the same time in different ways.

What is the need of DBMS ?

A database management system (DBMS) can help address the employee count scenario and a range of even more complex situations related to cost, order status or inventory management by presenting the same data to everyone in the business at the same time. A DBMS also eliminates the frustrating hunt for the right version of the right spreadsheet on a vast and disorganized network drive.

• As businesses grow, the volume of data they accumulate grows exponentially. Managing this data deluge becomes increasingly difficult just at the moment when superior data management becomes more important to business success.

• As businesses expand, more sophisticated tools are needed to manage data. Tools that serve start-ups well are overwhelmed by the demands faced by larger businesses.

• A database management system (DBMS) is a powerful tool used to store data, secure it, protect it and make it quickly available to people who need it.

• A DBMS enables a business to squeeze more value from the data it collects for improved decision-making.

What are Advantages and Disadvantages of DBMS?

The advantages and disadvantages of DBMS are as follows:
Reduced data redundancy
Reduced updating errors and increased consistency
Greater data integrity and independence from applications programs.
Improved data access to users through use of host and query languages.
Improved data security.
Reduced data entry, storage, and retrieval costs.
Facilitated development of new applications program.
Database systems are complex, difficult, and time-consuming to design.
Substantial hardware and software start-up costs.
Damage to database affects virtually all applications programs.
Extensive conversion costs in moving form a file-based system to a database system.
Initial training required for all programmers and users.

Database Models:

Database systems can be based on different data models or database models respectively. A data model is a collection of concepts and rules for the description of the structure of the database. Structure of the database means the data types, the constraints and the relationships for the description or storage of data respectively.

Hierarchical Model:
In a hierarchical DBMS one data item is subordinate to another one. This is called a parent-child relationship. The hierarchical data model organizes data in a tree-like structure.
One of the rules of a hierarchical database is that a parent can have multiple children, but a child can only have one parent. For example, think of an online store that sells many different products. The entire product catalog would be the parent, and the various types of products, such as books, electronics, etc., would be the children. Each type of product can have its own children categories.

Network Model:
In a network DBMS every data item can be related to many others ones. The database structure is like a graph. This is similar to the hierarchical model and also provides a tree-like structure. However, a child is allowed to have more than one parent. In the example of the product catalog, a book could fall into more than one category. The structure of a network database becomes more like a cobweb of connected elements

Relational Models:
In a relational DBMS all data are organized in the form of tables. This DBMS model emerged in the 1970s and has become by far the most widely used type of DBMS. Most of the DBMS software developed over the past few decades uses this model. In a table, each row represents a record, also referred to as an entity. Each column represents a field, also referred to as an attribute of the entity.
A relational DBMS uses multiple tables to organize the data. Relationships are used to link the various tables together. Relationships are created using a field that uniquely identifies each record. For example, for a table of books, you could use the ISBN number since there are no two books with the same ISBN. For a table of authors, you would create a unique Author ID to identify each individual author.

object Models:
The data is stored in the form of objects.Which are structures called classes that display the data within.The fileds are instances of these classes.the object oriented structure has the ability to handle the graphics,videos.This structure is popular for multimedia web based applications.It was designed to work with object-oriented programming languages such as like java..

Normalization is a systematic way of ensuring that a database structure is suitable for general-purpose querying and free of certain undesirable characteristics that could lead to a loss of data integrity.
The objectives of normalization:
Free the database of modification anomalies
Minimize redesign when extending the database structure
Make the data model more informative to users
Avoid bias towards any particular pattern of querying

In general, relational databases should be normalized to the “third normal form”.

Process of Normalization:
There are two main steps of the normalization process: eliminate redundant data (for example, storing the same data in more than one table) and ensure data dependencies make sense (only storing related data in a table). Both of these are worthy goals as they reduce the amount of space a database consumes and ensure that data is logically stored.
Formal technique for analyzing a relation based on its primary key and functional dependencies between its attributes.Often executed as a series of steps. Each step corresponds to a specific normal form, which has known properties.As normalization proceeds, relations become progressively more restricted (stronger) in format and also less vulnerable to update anomalies.

1 Normal form:
No Repeating Elements or Groups of Elements.
A relation in which intersection of each row and column contains one and only one value.
All key attributes get defined
No repeating groups in table
All attributes dependent on primary key

Second Normal form (2NF):
No Partial Dependencies on a Concatenated Key.
A relation that is in 1NF and every non-primary-key attribute is fully functionally dependent on the primary key (no partial dependency).

Third normal form(3NF):
No Dependencies on Non-Key Attributes.
A relation that is in 1NF and 2NF and in which no non-primary-key attribute is transitively dependent on the primary key.

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