Introduction of DBMS ?

 Introduction of Database Management System
» Objectives of Database Management System
» Functions of Database Management System
» Purpose of Database Management System
» Relational Database Overview
» Object Oriented Database Concept
» Data Warehousing

 

 

Introduction of Database Management System

A database management system is a complex set of software programs that controls the organization, storage, management and retrieval of data in a database. Database management system categorized according to the data structure or types. It is a set of pre written programs that are use to store, update and retrieve a database. The database management accepts request for data from the application program and instructs the operating system to transfer the appropriate data.

Objectives of Database Management System

An expression of database management system objectives serves and focuses attention on the needs of the using environment and the system and administrative requirements for meeting those needs. Some objectives of database management system derive directly from the assumed context of organization and management information system.

Shareability
An ability to share data resources is a fundamental objective of database management. Rather far reaching ramifications stem from the stated objectives of shareability

- Serving different types of users with varying skill levels.
- Handling different user views of the same stored data.
- Combining inter related data.
- .setting standards.
- Controlling concurrent updates so as to maintain data integrity.
- Co-ordinating restart and recovery operations across multiple users.

Availability
Availability means bringing the data of an organization to the user of that data. The system which manages data resources should be easily accessible to the people within organization – making the data available when and where it is needed and in the manner and from in which it is needed. Availability refers to both the data and the database management system which delivers the data. Availability function makes the database available to users defining and creating a database and getting data in and out of the database. These are the direct function performed by a database management system.

Evolvability
Evolvability refers to the ability of the database management system to change in response to growing user needs and advancing technology. Evolvability is the system characteristics system that enhances the future availability of the data resources. Evolvability is not the same as expandability or extensibility, which imply extending or adding to the system, which then grows ever larger. Evolvability covers expansion or contraction, both of which may occur as the system changes to fit the ever changing needs and desires of the using environment.

Adaptability
Adaptability is a more advanced form of evolvability in which built in algorithms enable a system to change itself, rather than having a change made to it. Adaptability involves purposive, self organizing, self controlling behavior, that is, self regulation towards a single criterion of success, it is an ultimate long term survival. System exhibiting adaptive behavior actively seeks a particular state or goal by changing itself in response to change in it self or its environment.

Integrity
The three primary facets of database integrity are.

- Protecting the existence of the database.
- Marinating the quality of the database.
- Ensuring the privacy of the database.

In developing database management system, the accountant’s concept of internal control has been practically ignored. Computer specialist need such concept to improve database integrity and enhance management confidence.

Functions of Database Management System

The name database management was chosen recognizing that the different names are in use and different types of system exist. Substantial generalization is assumed in any database management system of interest without using it generalized data is referred over information for the various reasons.

- Define, acquire and retire data according to the user needs.

- Provide tools to access and update the data and produce reports.

- Inform and assist users in planning and using data resources and database management tools.

- Maintain database integrity protecting its existence, maintain its quality and controlling access to private data.

- Monitor operations for efficient performance and integrity threats.

- It provides a building block in constructing data processing system for application requiring database access- MIS or system for the accounting, production and inventory control or customer support.

- It helps the DBA perform certain managerial duties.

Purpose of Database Management System

The purpose of database management system is to store and retrieve the information in an efficient manner. The most important duty of a database is to protect the data. Creating is also one of the purposes of the database management system.

Creating
The needed information which is to be stored in the database is created first using the appropriate software.

Storing
The created data are then stored up in the appropriate location in the database file.

Protecting
The most important duty of the database is to protect the data stored.

Retrieving
Database management system derives from the data a logical record needed by the application program.

Conclusion
We have seen briefly about the database management systems various objectives, functions and purpose which provide a convenient accessibility in managing the database of the management.

Entity relationship diagram
There are two entities; both of them are of the person type. There is a relationship called, is-married-to between these two persons. In this relationship, each of these two person entities has a role. One person plays the role of husband and another person plays the role of wife.

The Entity- Relationship (ER) diagram
One of the key techniques in ER modeling is to document the entity and relationship types in a graphical form called, entity relationship ER diagram mention figure is a typical ER diagram. The entity types such as EMP and depicted as rectangular boxes, and the relationship types such as WORK FOR are depicted as diamond shaped box. The value sets domains such as EMP NAME and PHONE are depicted as circles, while attributes are the mappings from entity and relationship types to the value sets. The cardinality information of relationship is also expressed. For example I or N on the lines between the entity types and relationship types indicated the upper limit of the entities of that entity type participating in that relationship.

Relational Database Overview

A database is a means of storing information in such a way that information can be received from it. In simplest terms, a relation database is one that present information in tables with row and columns. A table is referred as a relation in the sense that is a collection of objective of the same type (rows).

Data in a table can be related according to common keys or concepts, and the ability to retrieve related data from a table is the basis for the term relation database. A database management system handles the way data is stored, maintained, and retrieved. In the case of relationship database management system performs these tasks. Database management system as used in this book is a general term that includes RDBMS.

Integrity rules

Relation table follow certain integrity rules to ensure that the data they contain stay accurate and are always accessible. First, the rows in a relational table should all be distinct. If there are duplicate rows, there can be problem resolving which of two possible selections the correct one is. For most DBMS the user can specify that duplicate rows are not allowed, and if that is done, the DBMS will prevent the addition of any rows that duplicate an existing row. A second integrity rule of the traditional relational model is that column values must not be repeating groups or arrays. A third aspect of data integrity involves the concept of a null valve. A database takes care of situation where data may not be available by using a null value to indicate that a value is missing it does not equate to a blank or zero. A blank is considered equal to another blank, a zero is equal to another zero, but two null values are not considered equal.

Object Oriented Database Concept

Agenda

• Database
• Manipulation of database
• Types of database
• Object oriented database
• Basic concept of database management system (DBMS)
• Common features of old and new database
• The object oriented data model
• Object oriented language
• Some of the approaches to make object persistent

Database

A database is repository of collection of related data and facts, it arranges them in a specific structure the entire collection or related data in one table is referred to as file or a table. Each row in a table represents a record, which is a set of data for each database entry. Each table column represents a field, which groups each piece or item of data among the records into specific categories or types of data.

Manipulation of Database

We may manipulate the database in one or more of the following ways.
• Searching
• Sorting
• Merging
• Performing calculation on data
• Filtering
• Editing the database
• Report generation

Types of Database

• Flat- file database
• Relational database
• Hierarchical database
• Network database
• Object oriented database

Basic concept of Database Management Systems (DBMS)

A DBMS is a program, or collection of programs that allows any number of users to access data, modify it (if necessary) and construct simple and complex requests to abtain and work with selected records. The biggest asset of the DBMS , especially when it is running on powerful hardware, can find any speak of data in an enormous database in minutes- sometimes even seconds or fractions of a second. The management tasks in a DBMS fall into one of the following three general categories.

1. Entering data into the database.
2. Recording records in the database.
3. Obtaining subsets of the data.

Common features of the old database are

• Uniformity
• Record orientation
• Small data items
• Atomic fields

Uniformity
All the similarly sutured data items have the same size (in bytes).

Record orientation
The basic data items consist of fixed length records.

Small data items
Each record is mostly short.

Atomic fields
Field within the record are short and of fixed length. Each fixed length holds only atomic values. The database introduced recently may fail to have at leas one of the preceding features.

The new database applications include the following:

CAD (computer aided design)
CAD database stores data pertaining to engineering design including the components of the items being designed, the relationship between the components etc.
A CASE database stores data required to assist S/W developers. The data include.

1. Sources code.
2. Definition and use of variable.
3. Dependencies among software modules.
4. History of software system.

Multimedia databases
Multimedia database contains images, spatial data, audio, video, etc.

Hypertext database
Hypertext database supports the ability to retrieve document based on links and to query documents.

Object - oriented database
An object oriented database is a newer structure that has been generating a great deal of interest in recent years. It represents very different approach to the way data is treated by database developers and users. The object oriented structure groups data item and their associated characteristics, attributes, and procedures into complex items called objects. Physically an object can be anything a product, or event such as a house, an appliances, an art piece, a customer complaints, or even a purchase, an objects is defined by its characteristics attributes and procedures. An object characteristics can be text, sound, graphics, and video. Examples of attributes might be color, size, style, quantity, and price. A procedure refers to the processing or handling that can be associated to the object.

The Object Oriented Data Model

1. Object structure
2. Object classes
3. Inheritance
4. Multiple
5. Object identity
6. Object containment

Object oriented languages
The concept of object oriented data model are incorporated into language that is used to manipulate the.

Possible languages into which the object oriented feature can be integrated are:
• Data manipulation language.
• Persistent programming languages.

Persistent programming languages
Object oriented programming language can be extended to deal with database such languages are called persistence programming languages.

Persistent data
Data that continue to exist even after the program that created it has terminated.

Persistence of objects
Object oriented programming language has the concept of objects, which are transient i.e. they vanish when the program terminates. If we wish to turn such a language into a database programming language, first step to provide a way to make objects persistent.

Data Warehousing

Advantages of Data Warehouse

A data warehouse provides a common data model for all data of interest regardless of the data’s source. This makes it easier to report and analyze information than it would be it multiple data models where used to retrieve information such as sales invoices order receipts, general ledger charger, etc.

Prior to loading data into the data warehouse, inconsistence are identified and resolved. This greatly simplifies reporting and analysis.

Information in the data warehousing is under the control of data warehouse users so that even if the source system data is purged over time, the information in the warehouse can be stored safely for extended period of time. Data warehousing can work operational system, data warehousing provide retrieval of data without slowing down operational system.

Data warehouse facilitate decision support system applications such as trends report ( e.g the items with the most sales in a particular area within the last two years),exception reports that show actual performance versus goals, consolidated /standardized comprehensive, rapidly available information.

Features of Data Mining

i) Provides insight into hidden patterns and relationships in your data.
A classic example of data mining is a retailer who uncovers a relationship between sales of diapers and beer on Sunday afternoons- two items you wouldn’t normally consider as linked. The explanation is that husbands who are sent out to pick up a fresh supply of diapers are also likely to pick up some beer while they happen to be in the store – something that hadn’t been recognized as a significant sales driver before data mining uncovered it.

ii) Enables you to exploit these correlations to improve organizational performance.
Continuing the example above, very often retailers act on the relationships they discover by using tactics such as placing linked items together on end-of-isle displays as a way to spur additional purchases. All organizations can benefit from acting in a similar way – using newly discovered patterns and correlations as the basis for taking action to improve their efficiency and effectiveness.

iii) Provides indicators of future performance.
“Those who do not learn from history are doomed to repeat it” is a famous quote from philosopher George Santayana. In the case of data mining, being able to predict outcomes based on historic data can dramatically improve the quality and outcomes of decision making in the present. As a simple example, if the best indicator of whether a customer will pay on time turns out to be a combination of their market segment and whether or not they have paid previous bills on time, then this information you can usefully benefit from in making current credit decisions.

Advantages of Data Mining

Marketing / retailing
Data mining can aid direct marketers by providing them with useful and accurate trends about their customer’s purchasing behavior. Based on these trends, marketers can direct their marketing attentions to their customers with more precision. For example, marketers of a software company may advertise about their new software to consumers who have a lot of software purchasing history. In addition, data mining may also help marketers in predicting which products their customers may be interested in buying. Through this prediction, marketers can surprise their customers and make the customer's shopping experience a pleasant one.

Retail stores can also benefit from data mining in similar ways. For example, through the trends provided by data mining, the store managers can arrange shelves, stock certain items, or provide a certain discount that will attract their customers.

Banking / crediting
Data mining can assist financial institution in areas such as credit reporting and loan information for example, by examining previous customers with similar attributes, a bank can estimate the level of risk associated with each given loan. In addition, data mining can also assist credit cards issuers in detecting potentially fraudulent credit card transaction. Although the data mining technique is not 100% accurate in its prediction about fraudulent charges, it does help the credit card issuers reduce their losses.

Law enforcement
Data mining can aid law enforcers in identifying criminal suspects as well as apprehending these criminal by examining trends in location, crime type, habit, and other patterns of behaviors.

Researchers
Data mining can assist researchers by speeding up their data analyzing process thus, allowing them more time to work on other projects.