Structure of DBMS

Structure of DBMS

The structure of DBMS typically based on the relational data model . The following diagram shows typically DBMS based on the relational data model. The DBMS access SQL commands and generated a form of variety of user interfaces and produce query evaluation plan , Executes these plans against the database and returns the answers. When a user issues a query ,the parser can receive  the query and it is presented to query optimizer  which uses information about how data is stored in the database and produce efficient execution  plan for evaluating the query operator. An execution plan is the blue print for evaluate in the query and usually representation as a pre of relational operator.

            The code that implements with relational operator on the top of the file access methods layer. This layer includes a variety of software for supporting of concepts of files, in DBMS file is collection of records or pages. This layer typically supports as a heap file  as well as Indexing in addition to keeping the track of records or pages in a file. In this layer organize the information with in the pages. The file and access methods layer code sits on the top of the buffer manager  , which brings pages in from the disk to main memory . The main memory has needed in response to read requests.

            The lowest layer of DBMS software  management space on disk where the data is stored and high layer allocated and reallocated read and write pages through this layer can call the disk manager. In DBMS supports concurrency control and crash recovery manager by carefully scheduling user request and maintain a log of requests in database. DBMS components associated with concurrency control and recovery includes the transaction manager which ensures that transaction requests end release logs to a suitable locking protocol and schedule the execution transaction.

STRATEGY OF DATABASE PLANNING:

STRATEGY OF DATABASE PLANNING:

Data must be viewed as a corporate resource and other corporate resources must be devoted to the development, implement and use of  one or more databases. Database planning is strategy corporate effort to determine the information needs of the organization form extended period into the future. A successful database planning project will precede operational project to design and implement new databases to satisfy the organizational information needs.

The need for database planning: Database planning is directed by the information needs of the organization which in turn or determined by the company’s business plan . the process is shown in the below diagram.

Business Plan à Information Needs à Database Plan à Database Development Projects.

The corporation formulates has its strategy business plan for the next 5 (five) years . Accomplishing the objectives of this plans depends on the availability of certain  identify types of information . The information can we obtained only if the data sources  are identified in the database planning,  or in place . This indicates the needs of the database development projects which create new database or enhance or integrate existing databases. Database planning has significant advantages James cites  several advantages of formal information resource plan.

1. It expresses management current understanding of the information resources.
2. It identifies and justifies resources requirements, helping ensure that the resources will be available.
3. It identifies and justifies for effective resources management including the collaboration among departments or diligence with in the organization.
4. It  Specifies  action plans for achieving objectives.
5. It can provide a powerful stimulus and sense of direction to employees at all levels.

Focusing these effects increasing their productivity and making them feel that they are a genuine part of the organization/ enterprise.

Range of Database Approach.

Range of Database Approach.

In database approach the range of database application of from single user to multi user database . Generally we have seven database approaches. These are

Personal Database approach: Personal database approach is designed to support to store and to maintain the personal information. It can access by one user only. In general we can store personal database in personal computers like laptops, cellular phones etc. We have major problem with personal database approach that is it does not allow sharing of the data i.e. the personal database is  working based on the stand-alone mode.

Eg:

Work group database approach: In work group database approach , consists 20-25 members those team of people will develop a database of an organization . The work group database is designed to support to maintain database by a group of people.

            Work group database provides data sharing  . In general work group database in LAN  group network  where database is available in one system  this system is known as database Server .Database server is connected with 10 or more than 10 users .This type of architecture  is known as one type of client/server architecture . Work group databases are sold to database vendors those vendors again sold to different customers and users.

Eg.

Departmental database approach: Departmental database approach is designed to support to maintain departmental wise activities in an organization. It consist department information , procedures and functions.

            In departmental database consist 50-100 persons to perform a task. In an organization contain its department  database server in an organization . The department database are connected to maintain from the main server to connect the database departmental database server , distributed the information to department and users . This technology is called as two tier database architecture.

Eg:

Enterprise database approach: Enterprise database  approach is designed to support to maintain organization database . It not only control the organizational database but also making decisions to support the database . It perform all the activities of an organization. The education of enterprise database approach two major departments these are

1. Enterprise Resource Planning System (ERPS)
2. Data warehousing .

ERPS is developed from MRP(Material Requirement  Planning ) system .These system contains some functions such as how to distribute the data to entire organization and how to control the flow of data in an  enterprise / organization .In  an enterprise database we have entire organization database or information and historical information about the organization and collaboration organization information such enterprise database organization is known as data ware housing.

Eg:

Internet: Using Internet  protocols to establish  connection  and  access company data or information by any person or user  who may have or may not have relation with that organization is known as Internet.

Eg: To access data by external person or user who are related to other company is known as internet. i.e. Any student can access the data of certain University or Organization  is called Internet process.

Intranet: Using Internet  protocols to establish  connection  and  access company data or information by limited  persons or users  who are related  with that organization is known as Intranet.

Eg: To access data by staff and students etc  who are related to the same  company is known as intranet. i.e. Any student and staff  can access the data of certain University or Organization  is called Intranet process.

Extranet:Using Internet  protocols to establish  connection  and  access company data or information by company directors, customers, dealers and legal advisers etc who have a  relation with that organization is known as Extranet.

Eg: In Hyderabad .We have  our University, Our college is in Nizamabad and Our college is affiliated  or related to that University . Every University have their own database for maintaining the university

Our college is connected with  university database through internet in order to retrieve college rules and regulations this concept is known as Extranet.

MAJOR COMPONENTS OF DATABASE ENVIRONMENT.

 Strong Database Environment consist of 9 (Nine) major components to maintain the database successful. The Major components of database environment are

CASE Tools : (Computer Aided Software Engineering Tools) .CASE Tools are predefined tools. These are automatically designed the database in database approach.

Repository: It is a centralized location of data definitions, data relationships, reports, formats and other system components and descriptions of the data is called Repository.

DBMS: DBMS (Database Management System) : It is a Mechanism , A system which is consist a set of well defined programs to  create, store, Delete, manipulate and retrieve  the data in an organization by using File Operations like create a file , update file, delete file and insert file efficiently  is known as DBMS.

Database A set  of the interrelated data of an organization is a database. Usually it design to meet the information of multiple users in an organization .The repository  contains the definitions and structure of the data where as the database contain the occurrence of the data.

Application Programs: A computer programs which is used to create and maintain the database to provide the information to users is an application programs.

User Interface: Languages, Menus, Commands and other facilities which are used to interact with the computers by user is a user interface. Generally this component is work as a interface with each and every component in an database environment.

Database Administrator:  (DBA):  DBA is a person who has a responsible for overall information resources  and central control  of  an organization .

System Developers:  These are persons  such as system programmers and analysts , who designed new application programs is called system developers.

End Users: End user is a person who insert , delete and modify the data in the database and who request information from database is known as end user.

COSTS & RISKS are involved in dbms

COSTS &  RISKS involved in database development:

In database approach in order to maintain or develop database we should take a risk and we should invest money , time and environment. Database approach when we develop a new database or when we maintain an existing database we should consider the following points.

à New specialized persons.

à Installation and manage cost and complexity.

à Conversion costs.

à Need for explicit back up and recovery.

à Organizational conflict.

New specialized persons: Organization adopted the database approach to maintain individuals to design and implement database for that an organization provides DBA and manage a staff of  new people because there is a rapid changes in the technology .New people will have to be retrained or upgraded their knowledge in database approach in an organization required specialized  skill persons to maintain the database.

Installation and manage cost and complexity: A multi user database management system is a large and complex . It  has a high level install cost requires a staff to trained persons to install and operate . It also require professionals to maintain annual maintenance and cost .These systems are require to install new software to upgrade the database for that we should take a risk to modify Hard ware and data communications in an organization.

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DBA (DataBase Administrator)

DBA (Database Administrator)

One of the main reasons for using DBMS to having central control of both the data and the programs that access  the data , the person who has such central control  over the system is called the database administrator (DBA) . The functions of DBA  as follows

Schema Definition: The DBA creates the original database schema   by writing a set of Definitions that are translated by the compiler to a set of tables that are stored in permanently in the data dictionary.

Storage structure and access method definition: The DBA creates appropriate storage structures to access methods by writing  a set definitions by translated these are to data storage and data definition language compiler.

Schema physical organization modification: programmers accomplish the relatively rare modifications either to the data schema or to the description of the physical storage structure . Organization writing a set of definitions that are used either the DDL compiler or the data storage and data definition language compiler to generate modifications to the appropriate internal system table.

Granting of authorization for data access: The granting of different types of authorization allows the DBMS administrators to regulate which parts of the database various users can access the authorization  information is kept in a separate structure that is consulted by  the database systems when ever access to the user data is attempt in the system.

 Integrity constraints specification: The   data value stored in the database must satisfied certain consistency constraints . The integrity constraints are must specify external system of DBA. These are kept in a special system structure that is consulted by database system when ever update in the  system.

DBA Goals:

Protecting  the database from unauthorized users and also to handle total data from the table  in this way the DBA has two types of goals. These are

Integrity : It is considered with making certain operations which are performed by the users or correct and maintain the data consistency in these ways the DBA should be maintained  a key values to the related table.

 Security: It is considered with limiting users to performing only  certain operations that are allowed the DBA should provide security for data accessing from the database.

DATA SHARING:

DATA SHARING:

The most significant  difference between a file based systems and database systems is Data sharing. Data sharing also requires a major change in the way of data are handled and managed with in the organization.  Data sharing are of 3 (three) types. They are

1. Sharing Data between functional units.
2. Sharing data between management units.
3. Sharing data between geographically dispersed location.

1. Sharing data between functional units: The term  data sharing suggests that people in different functional areas are use a common pool of data. Each of these are own applications without data sharing the marketing group may have their data files. The purchasing group like accounts group their own data files and marketing group have their own data files and so on… each group benefits from its own data. Eg diagram.

In contrasts the effect of combining data into database is synergistic that is the combined data are more valuable then the some of the data in separated files .Not only does each group continue to have access to its own data but with in a reasonable limits and control they have access to other data as well. In this environment the marketing department for eg: Is better of because it has access to data from purchasing, especially product evolution which provide valuable input for marketing campaigns.

2. Sharing data between Management units: Diagram

 Different levels of users also need to share data . The three different levels of users are 1. Operation level, 2. Middle Management Level, 3. Execute level.

These three levels are corresponded to the three different types of system these are Electronic data processing, Management information system, and  Decision support system.

EXECUTIVE  à Decision Support System à Strategic Reports, Queries, Analysis.

MIDDLE MANAGEMENT à Management Information System à Management reports of functional areas.

Operations à Electronic Data Processing System  à Transaction file, Maintenance Processing and control reports.

The relationships of  the above three systems  have to different management levels is shown in diagram .These levels of users and system naturally requires three different types of data. The user at the operational level needs data for transaction processing that is include data for new accounts are changes to an existing accounts management. The management information system level utilize summaries to indicate which sales representatives were most or least productive and executives at highest level used decision support system to discover long term trends that apply to their own corporation as well as to identify the economic social and political environment in which they operate. The DSS means Decision Support System help them makes the decisions such as building a new factory starting or dropping a product line and DSS uses summery data from with in the company as well as market and author data form outside sources.

3.Sharing data between geographically dispersed location: A company  with several

locations has important data distributed over a valid geographically area sharing .   these data is a significant  problems. A centralized database is physically contained to a single location  controlled by a single computer that is Personal computer  most  function for which databases are created and accomplished more easily . If the database is centralized and it is easily to update and back up , recovery and control access to a database . If we know database exactly where it is and what’s software control it and identify the remote place where it is located.

European Public Policy Blog: Supporting research and innovation in Europe’s universities

European Public Policy Blog: Supporting research and innovation in Europe’s universities

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European Public Policy Blog: DatenDialog - Big Tent goes to Berlin

European Public Policy Blog: DatenDialog - Big Tent goes to Berlin

database sharing

DATA SHARING:

The most significant  difference between a file based systems and database systems is Data sharing. Data sharing also requires a major change in the way of data are handled and managed with in the organization.  Data sharing are of 3 (three) types. They are

1. Sharing Data between functional units.
2. Sharing data between management units.
3. Sharing data between geographically dispersed location.

Sharing data between functional units: The term  data sharing suggests that people in different functional areas are use a common pool of data.