Definitions Of Key Terms

Definitions of key terms Database: An organized collection of logically related data Eg:- Student information system Roll no

Name

Total

Percentage(%)

123

ABC

412

69

345

CBA

456

72

313

PQR

512

87

Data: Facts, text, graphics, images, sound, and video segments that have meaning in the user environment. Information: Data that have been processed in such a way that they can increase the knowledge of the person who uses it. Metadata: Data that describes the properties or characteristics of other data. Database application: An application program (or set of related programs) that is used to perform a series of database activities (create, read, update, and delete) on behalf of database users. Data warehouse: An integrated decision support database whose content is derived from the various operational databases. Constraint: A rule that cannot be violated by database users. Legacy data: Data contained by a system used prior to the installation of a new system.

Differences of Data dependence; data independence: With data dependence, data descriptions are included with the application programs that use the data, while with data independence the data descriptions are separated from the application programs. Data warehouse; data mining: A data warehouse is an integrated decision support database, while data mining (described in the chapter introduction) is the process of extracting useful information from databases. Data; information: Data consist of facts, text, and other multimedia objects, while information is data that have been processed in such a way that it can increase the knowledge of the person who uses it. Repository; database: A repository is a centralized storehouse for all data definitions, data relationships, and other system components, while a database is an organized collection of logically related data. Entity; enterprise data model: An entity is an object or concept that is important to the business, while an enterprise data model is a graphical model that shows the high-level entities for the organization and the relationship among those entities.

Data warehouse; ERP system: Both use enterprise level data. Data warehouses store historical data at a chosen level of granularity or detail, and are used for data analysis purposes, to discover relationships and correlations about customers, products, and so forth that may be used in strategic decision making. ERP systems integrate operational data at the enterprise level, integrating all facets of the business, including marketing, production, sales, and so forth

Range of database application Personal computer databases – No graphical representation only limited can be stored Workgroup database – Small group of people working for particular project, database is shared among 5-25 people and use 2-tier architecture. Eg: several scientists performing research on a new drug. Department database – 25- 100 people work in this type of database and use 3-tier architecture. Eg: database used by the human resources department of a large hospital. Enterprise database – More than 100 people work. Eg: the database supporting the SAP enterprise information system. Internet, intranet, extranet databases – More than 1000 people work on web server Intranet- within the organization, extranet-giving access to the people who are not part of the organization.

Components of database DB Administrat

CASE tools

Reposito ry

System declarer

User interfac e

DBMS

End user

Applica tion/pro gram

Data base

CASE tools: automated tools used to design databases and database applications. Repository: centralized storehouse of data definitions. Database management system (DBMS): commercial software used to define, create, maintain, and provide controlled access to the database and the repository. Database: organized collection of logically related data. Application programs: computer programs that are used to create and maintain the database. User interface: languages, menus, and other facilities by which users interact with the various system components. Data administrators: persons who are responsible for the overall information resources of an organization. System developers: persons such as systems analysts and programmers who design new application programs. End users: persons who add, delete, and modify data in the database and who request information from it.

Cost and risk of database approach 

New, specialized personnel



Installation and management cost and complexity



Conversion costs



Need for explicit backup and recovery



Organizational conflict

Evolution of database 1960s – Traditional files. 1970s – First generation; hierarchical and network databases. 1980s – Second generation; relational databases. 1990s – Third generation; object-oriented and object-relational databases. 2000s – Facility of providing advanced things like sound clips and so on.

Disadvantages of File processing system (FPS) •

Program data dependence

•

Duplication of data

•

Limited data sharing

•

Lengthy development time

•

Excessive cost maintenance

Potential benefits of the database approach are 1. Program-data independence: Data descriptions are not stored in the program, stored in the centralized location. 2. Minimal data redundancy: Unnecessary repetition of data when

compared to FPS, redundancy is reduced. Since redundancy is reduced we get consistent data. 3. Improved data consistency: Consistency is improved since redundancy is reduced. 4. Improved data sharing: The data can be shared by any no of programs. 5. Increased development productivity Some tools are available with in which we can design the program.so, there is no need to write the program from the beginning. 6. Enforcement standards: 7. Improved data quality: Imparting quality of data which is entered into the database by preceding. 8. Improved data accessibility and responsiveness: We can store the data into the database in a very simplified language called SQL (structured query language). 9. Reduced program maintenance: All the advantages will reduce the program maintenance.

Database development process SDLC: System development life cycle model Project identification & selection Project initiation& planning

Analysis

Logical design Physical design Implementati on Maintenance

•

Traditional method of converting or developing a system

•

It is also known as waterfall model or cascade model since every step is involved

Project identification •

There may be some drawbacks which are identified and made into a good project

•

New project is prepared

Project initializing •

We have to identify to which organization we are making a project

•

Here the draw backs will be identified

Analysis •

The project leader will go and interact with the person who uses the project

Logical design •

Putting a diagramatic representation what is going to be in the project. It will be in the form of menus, reports or forms

Physical design •

Have the database is going to be stored and reterived.It will be understood only by project manager.

Implementation •

All the information will be given to the programmer and he will write the coding, training the users, testing different data

Maintenance •

Any updations that should made or done will come under maintenance will be there till the project exist

•

Prototyping method

Analyses project

Convert into operational

Implement prototype

Initial requirement

Develop prototype

developing to working model

Enhance and revise the prototype

errors Improved prototype

Prototype: Prototyping is an iterative process of converting the initial requirements into a working model.

Architecture: Three tier Architecture:

• Conceptual schema • External or view schema • Physical schema Client server Architecture: when a request for a data by a client, it is served from a server through LAN or WAN or MAN Web server Architecture: A server which is large server, which a client is requesting for data, then it searches in application server if the data is not found in it then it is searched from web. Enterprise server Architecture: This process is used for large data and calculations like in mainframe computers.