Docstoc

Body

Document Sample
Body Powered By Docstoc
					                                    Introduction


       A database management system (DBMS) is a software package with computer

programs that control the creation, maintenance, and use of a database. It allows

organizations to conveniently develop databases for various applications by database

administrators (DBAs) and other specialists. A database is an integrated collection of data

records, files, and other objects. A DBMS allows different user application programs to

concurrently access the same database. DBMSs may use a variety of database models,

such as the relational model or object model, to conveniently describe and support

applications. It typically supports query languages, which are in fact high-level

programming languages, dedicated database languages that considerably simplify writing

database application programs. Database languages also simplify the database

organization as well as retrieving and presenting information from it. A DBMS provides

facilities for controlling data access, enforcing data integrity, managing concurrency

control, and recovering the database after failures and restoring it from backup files, as

well as maintaining database security.




Database servers are dedicated computers that hold the actual databases and run only the

DBMS and related software. Database servers are usually multiprocessor computers, with

generous memory and RAID disk arrays used for stable storage. Hardware database

accelerators, connected to one or more servers via a high-speed channel, are also used in



Eastwoods Professional College of Science and Technology                            Page 1
large volume transaction processing environments. DBMSs are found at the heart of most

database applications. DBMSs may be built around a custom multitasking kernel with

built-in networking support, but modern DBMSs typically rely on a standard operating

system to provide these functions.




Database Management Systems



       A database is a collection of related files that are usually integrated, linked or

cross-referenced to one another. The advantage of a database is that data and records

contained in different files can be easily organized and retrieved using specialized

database management software called a database management system (DBMS) or

database manager.




After reading this lesson, you should be able to:




      Define the term database management system (DBMS).

      Describe the basic purpose and functions of a DBMS.

      Discuss the advantages and disadvantages of DBMSs.




Eastwoods Professional College of Science and Technology                          Page 2
DBMS Fundamentals

       A database management system is a set of software programs that allows users to

create, edit and update data in database files, and store and retrieve data from those

database files. Data in a database can be added, deleted, changed, sorted or searched all

using a DBMS. If you were an employee in a large organization, the information about

you would likely be stored in different files that are linked together. One file about you

would pertain to your skills and abilities, another file to your income tax status, another

to your home and office address and telephone number, and another to your annual

performance ratings. By cross-referencing these files, someone could change a person's

address in one file and it would automatically be reflected in all the other files. DBMSs

are commonly used to manage:




      Membership and subscription mailing lists

      Accounting and bookkeeping information

      The data obtained from scientific research

      Customer information

      Inventory information

      Personal records

      Library information




Eastwoods Professional College of Science and Technology                            Page 3
DBMSs and File Management Systems

       Computerized file management systems (sometimes called file managers) are not

considered true database management systems because files cannot be easily linked to

each other. However, they can serve as useful data management functions by providing a

system for storing information in files. For example, a file management system might be

used to store a mailing list or a personal address book. When files need to be linked, a

relational database should be created using database application software such as Oracle,

Microsoft Access, IBM DB2, or FileMaker Pro.




The Advantages of a DBMS




Improved availability: One of the principle advantages of a DBMS is that the same

information can be made available to different users.




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, or in other words,

the need to repeat the same data over and over again. Minimizing redundancy can

therefore significantly reduce the cost of storing information on hard drives and other

storage devices. In contrast, data fields are commonly repeated in multiple files when a

file management system is used.



Eastwoods Professional College of Science and Technology                          Page 4
Accuracy: Accurate, consistent, and up-to-date data is a sign of data integrity. DBMSs

foster data integrity because 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.




Program and file consistency: Using a database management system, file formats and

system programs are standardized. This makes the data files easier to maintain because

the same rules and guidelines apply across all types of data. The level of consistency

across files and programs also makes it easier to manage data when multiple

programmers are involved.




User-friendly: Data is easier to access and manipulate with a DBMS than without it. In

most cases, DBMSs also reduce the reliance of individual users on computer specialists

to meet their data needs.




Improved security: As stated earlier, DBMSs allow multiple users to access the same

data resources. This capability is generally viewed as a benefit, but there are potential

risks for the organization. Some sources of information should be protected or secured

and only viewed by select individuals. Through the use of passwords, database

management systems can be used to restrict data access to only those who should see it.

Eastwoods Professional College of Science and Technology                            Page 5
The Disadvantages of a DBMS




There are basically two major downsides to using DBMSs. One of these is cost, and the

other the threat to data security.




Cost: Implementing a DBMS system can be expensive and time-consuming, especially in

large organizations. Training requirements alone can be quite costly.




Security: Even with safeguards in place, it may be possible for some unauthorized users

to access the database. In general, database access is an all or nothing proposition. Once

an unauthorized user gets into the database, they have access to all the files, not just a

few. Depending on the nature of the data involved, these breaches in security can also

pose a threat to individual privacy. Steps should also be taken to regularly make backup

copies of the database files and store them because of the possibility of fires and

earthquakes that might destroy the system.




Eastwoods Professional College of Science and Technology                           Page 6
                                           History




       Databases have been in use since the earliest days of electronic computing. Unlike

modern systems, which can be applied to widely different databases and needs, the vast

majority of older systems were tightly linked to the custom databases in order to gain

speed at the expense of flexibility. Originally DBMSs were found only in large

organizations with the computer hardware needed to support large data sets.




1960s Navigational DBMS

       As computers grew in speed and capability, a number of general-purpose database

systems emerged; by the mid-1960s there were a number of such systems in commercial

use. Interest in a standard began to grow, and Charles Bachman, author of one such

product, the Integrated Data Store (IDS), founded the "Database Task Group" within

CODASYL, the group responsible for the creation and standardization of COBOL. In

1971 they delivered their standard, which generally became known as the "Codasyl

approach", and soon a number of commercial products based on this approach were made

available.




Eastwoods Professional College of Science and Technology                             Page 7
       The Codasyl approach was based on the "manual" navigation of a linked data set

which was formed into a large network. When the database was first opened, the program

was handed back a link to the first record in the database, which also contained pointers

to other pieces of data. To find any particular record the programmer had to step through

these pointers one at a time until the required record was returned. Simple queries like

"find all the people in India" required the program to walk the entire data set and collect

the matching results one by one. There was, essentially, no concept of "find" or "search".

This may sound like a serious limitation today, but in an era when most data was stored

on magnetic tape such operations were too expensive to contemplate anyway. Solutions

were found to many of these problems. Prime Computer created a CODASYL compliant

DBMS based entirely on B-Trees that circumvented the record by record problem by

providing alternate access paths. They also added a query language that was very

straightforward. Further, there is no reason that relational normalization concepts cannot

be applied to CODASYL databases however, in the final tally, CODASYL was very

complex and required significant training and effort to produce useful applications.




       IBM also had their own DBMS system in 1968, known as IMS. IMS was a

development of software written for the Apollo program on the System/360. IMS was

generally similar in concept to Codasyl, but used a strict hierarchy for its model of data

navigation instead of Codasyl's network model. Both concepts later became known as

navigational databases due to the way data was accessed, and Bachman's 1973 Turing

Award award presentation was The Programmer as Navigator. IMS is classified as a



Eastwoods Professional College of Science and Technology                               Page 8
hierarchical database.IDMS and CINCOM's TOTAL database are classified as network

databases.




1970s relational DBMS

       Edgar Codd worked at IBM in San Jose, California, in one of their offshoot

offices that was primarily involved in the development of hard disk systems. He was

unhappy with the navigational model of the Codasyl approach, notably the lack of a

"search" facility. In 1970, he wrote a number of papers that outlined a new approach to

database construction that eventually culminated in the groundbreaking A Relational

Model of Data for Large Shared Data Banks.




       In this paper, he described a new system for storing and working with large

databases. Instead of records being stored in some sort of linked list of free-form records

as in Codasyl, Codd's idea was to use a "table" of fixed-length records. A linked-list

system would be very inefficient when storing "sparse" databases where some of the data

for any one record could be left empty. The relational model solved this by splitting the

data into a series of normalized tables (or relations), with optional elements being moved

out of the main table to where they would take up room only if needed.




Eastwoods Professional College of Science and Technology                            Page 9
       For instance, a common use of a database system is to track information about

users, their name, login information, various addresses and phone numbers. In the

navigational approach all of these data would be placed in a single record, and unused

items would simply not be placed in the database. In the relational approach, the data

would be normalized into a user table, an address table and a phone number table (for

instance). Records would be created in these optional tables only if the address or phone

numbers were actually provided.




       Linking the information back together is the key to this system. In the relational

model, some bit of information was used as a "key", uniquely defining a particular

record. When information was being collected about a user, information stored in the

optional tables would be found by searching for this key. For instance, if the login name

of a user is unique, addresses and phone numbers for that user would be recorded with

the login name as its key. This "re-linking" of related data back into a single collection is

something that traditional computer languages are not designed for.




       Just as the navigational approach would require programs to loop in order to

collect records, the relational approach would require loops to collect information about

any one record. Codd's solution to the necessary looping was a set-oriented language, a

suggestion that would later spawn the ubiquitous SQL. Using a branch of mathematics

known as tuple calculus, he demonstrated that such a system could support all the




Eastwoods Professional College of Science and Technology                             Page 10
operations of normal databases (inserting, updating etc.) as well as providing a simple

system for finding and returning sets of data in a single operation.




       Codd's paper was picked up by two people at Berkeley, Eugene Wong and

Michael Stonebraker. They started a project known as INGRES using funding that had

already been allocated for a geographical database project, using student programmers to

produce code. Beginning in 1973, INGRES delivered its first test products which were

generally ready for widespread use in 1979. During this time, a number of people had

moved "through" the group — perhaps as many as 30 people worked on the project,

about five at a time. INGRES was similar to System R in a number of ways, including the

use of a "language" for data access, known as QUEL — QUEL was in fact relational,

having been based on Codd's own Alpha language, but has since been corrupted to follow

SQL, thus violating much the same concepts of the relational model as SQL itself.




       IBM itself did one test implementation of the relational model, PRTV, and a

production one, Business System 12, both now discontinued. Honeywell did MRDS for

Multics, and now there are two new implementations: AlphoraDataphor and Rel. All

other DBMS implementations usually called relational are actually SQL DBMSs.


       In 1970, the University of Michigan began development of the MICRO

Information Management System based on D.L. Childs' Set-Theoretic Data model. Micro

was used to manage very large data sets by the US Department of Labor, the U.S.

Environmental Protection Agency, and researchers from the University of Alberta, the

Eastwoods Professional College of Science and Technology                            Page 11
University of Michigan, and Wayne State University. It ran on IBM mainframe

computers using the Michigan Terminal System. The system remained in production until

1998.




Late-1970s SQL DBMS

         IBM started working on a prototype system loosely based on Codd's concepts as

System R in the early 1970s. The first version was ready in 1974/5, and work then started

on multi-table systems in which the data could be split so that all of the data for a record

(some of which is optional) did not have to be stored in a single large "chunk".

Subsequent multi-user versions were tested by customers in 1978 and 1979, by which

time a standardized query language – SQL – had been added. Codd's ideas were

establishing themselves as both workable and superior to Codasyl, pushing IBM to

develop a true production version of System R, known as SQL/DS, and, later, Database 2

(DB2).


         Many of the people involved with INGRES became convinced of the future

commercial success of such systems, and formed their own companies to commercialize

the work but with an SQL interface. Sybase, Informix, NonStop SQL and eventually

Ingres itself were all being sold as offshoots to the original INGRES product in the

1980s. Even Microsoft SQL Server is actually a re-built version of Sybase, and thus,

INGRES. Only Larry Ellison's Oracle started from a different chain, based on IBM's

papers on System R, and beat IBM to market when the first version was released in 1978.


Eastwoods Professional College of Science and Technology                            Page 12
          Stonebraker went on to apply the lessons from INGRES to develop a new

database, Postgres, which is now known as PostgreSQL. PostgreSQL is often used for

global mission critical applications (the .org and .info domain name registries use it as

their primary data store, as do many large companies and financial institutions).




          In Sweden, Codd's paper was also read and Mimer SQL was developed from the

mid-70s at Uppsala University. In 1984, this project was consolidated into an

independent enterprise. In the early 1980s, Mimer in c introduced transaction handling

for high robustness in applications, an idea that was subsequently implemented on most

other DBMS.




1980s object-oriented databases

          The 1980s, along with a rise in object oriented programming; saw a growth in

how data in various databases were handled. Programmers and designers began to treat

the data in their databases as objects. That is to say those if a person’s data were in a

database, that person’s attributes, such as their address, phone number, and age, werenow

considered to belong to that person instead of being extraneous data. This allows for

relations between data to be relations to objects and their attributes and not to individual

fields.




Eastwoods Professional College of Science and Technology                            Page 13
       Another big game changer for databases in the 1980s was the focus on increasing

reliability and access speeds. In 1989, two professors from the University of Wisconsin at

Madison published an article at an ACM associated conference outlining their methods

on increasing database performance. The idea was to replicate specific important, and

often queried information, and store it in a smaller temporary database that linked these

key features back to the main database. This meant that a query could search the smaller

database much quicker, rather than search the entire dataset. This eventually leads to the

practice of indexing, which is used by almost every operating system from Windows to

the system that operates Apple iPod devices.




21st century NoSQL databases

       In the 21st century a new trend of NoSQL databases was started. Those non-

relational databases are significantly different from the classic relational databases. They

often do not require fixed table schemas, avoid join operations by storing denormalized

data, and are designed to scale horizontally. Most of them can be classified as either key-

value stores or document-oriented databases.


       In recent years there was a high demand for massively distributed databases with

high partition tolerance but according to the CAP theorem it is impossible for a

distributed system to simultaneously provide consistency, availability and partition

tolerance guarantees. A distributed system can satisfy any two of these guarantees at the

same time, but not all three. For that reason many NoSQL databases are using what is


Eastwoods Professional College of Science and Technology                            Page 14
called eventual consistency to provide both availability and partition tolerance guarantees

with a maximum level of data consistency.


       The most popular software in that category include: memcached, Redis,

MongoDB, CouchDB, Apache Cassandra and HBase, that all are open-source software

products.




XML databases

       A subset of NoSQL databases are XML databases. They all use industry standard

XML data storage format. XML is open, machine-readable and cross-platform data

format widely used for interoperability among different IT systems. XML database

software market is dominated by commercial vendor products.


       Software in this category include: Basex, Clusterpoint Server, eXist, MarkLogic

Server, MonetDB/XQuery, Oracle, Sedna.All XML databases can be attributed to

document-oriented databases.




Current trends

       In 1998, database management was in need of a new style of databases to solve

current database management problems. Researchers realized that the old trends of

database management were becoming too complex and there was a need for automated

configuration and management. SurajitChaudhuri, Gerhard Weikum and Michael

Eastwoods Professional College of Science and Technology                           Page 15
Stonebraker were the pioneers that dramatically affected the thought of database

management systems. They believed that database management needed a more modular

approach and there were too many specifications needed for users. Since this new

development process of database management there are more possibilities. Database

management is no longer limited to “monolithic entities”. Many solutions have been

developed to satisfy the individual needs of users. The development of numerous

database options has created flexibility in database management.




       There are several ways database management has affected the field of technology.

Because organizations' demand for directory services has grown as they expand in size,

businesses use directory services that provide prompted searches for company

information. Mobile devices are able to store more than just the contact information of

users, and can cache and display a large amount of information on smaller displays.

Search engine queries are able to locate data within the World Wide Web. Retailers have

also benefited from the developments with data warehousing, recording customer

transactions. Online transactions have become tremendously popular for e-business.

Consumers and businesses are able to make payments securely through some company

websites.




Eastwoods Professional College of Science and Technology                       Page 16
Components

              DBMS engine accepts logical requests from various other DBMS

               subsystems, converts them into physical equivalents, and actually accesses

               the database and data dictionary as they exist on a storage device.

              Data definition subsystem helps the user create and maintain the data

               dictionary and define the structure of the files in a database.

              Data manipulation subsystem helps the user to add, change, and delete

               information in a database and query it for valuable information. Software

               tools within the data manipulation subsystem are most often the primary

               interface between user and the information contained in a database. It

               allows the user to specify its logical information requirements.

              Application generation subsystem contains facilities to help users

               develop transaction-intensive applications. It usually requires that the user

               perform a detailed series of tasks to process a transaction. It facilitates

               easy-to-use data entry screens, programming languages, and interfaces.

              Data administration subsystem helps users manage the overall database

               environment by providing facilities for backup and recovery, security

               management, query optimization, concurrency control, and change

               management.




Eastwoods Professional College of Science and Technology                             Page 17
Modeling language

       A modeling language is a data modeling language to define the schema of each

database hosted in the DBMS, according to the DBMS database model. Database

management systems (DBMS) are designed to use one of five database structures to

provide simplistic access to information stored in databases. The five database structures

are:


              the hierarchical model,

              the network model,

              the relational model,

              the multidimensional model, and

              The object model.


       Inverted lists and other methods are also used. A given database management

system may provide one or more of the five models. The optimal structure depends on the

natural organization of the application's data, and on the application's requirements,

which include transaction rate (speed), reliability, maintainability, scalability, and cost.




The hierarchical structure

       The hierarchical structure was used in early mainframe DBMS. Records’

relationships form a treelike model. This structure is simple but nonflexible because the

relationship is confined to a one-to-many relationship. IBM’s IMS system and the RDM



Eastwoods Professional College of Science and Technology                              Page 18
Mobile are examples of a hierarchical database system with multiple hierarchies over the

same data. RDM Mobile is a newly designed embedded database for a mobile computer

system. The hierarchical structure is used primarily today for storing geographic

information and file systems.


       Hierarchical model redirects here. For the statistics usage, see hierarchical linear

modeling.


       A hierarchical database model is a data model in which the data is organized into

a tree-like structure. The structure allows representing information using parent/child

relationships: each parent can have many children, but each child has only one parent

(also known as a 1-to-many relationship). All attributes of a specific record are listed

under an entity type.




                                Example of a hierarchical model

Eastwoods Professional College of Science and Technology                           Page 19
       In a database an entity type is the equivalent of a table. Each individual record is

represented as a row, and each attribute as a column. Entity types are related to each other

using 1:N mappings, also known as one-to-many relationships. This model is recognized

as the first database model created by IBM in the 1960s.




       Currently the most widely used hierarchical databases are IMS developed by IBM

and Windows Registry by Microsoft.




The Network Structure




       The network structure consists of more complex relationships. Unlike the

hierarchical structure, it can relate to many records and accesses them by following one

of several paths. In other words, this structure allows for many-to-many relationships.




       For computer network models, see network topology, packet generation model

and channel model.




Eastwoods Professional College of Science and Technology                            Page 20
        The network model is a database model conceived as a flexible way of

representing objects and their relationships. Its distinguishing feature is that the schema,

viewed as a graph in which object types are nodes and relationship types are arcs, is not

restricted to being a hierarchy or lattice.




                                    Example of a Network Model.




        The network model's original inventor was Charles Bachman, and it was

developed into a standard specification published in 1969 by the CODASYL Consortium.



Eastwoods Professional College of Science and Technology                            Page 21
The relational structure




       The relational structure is the most commonly used today. It is used by

mainframe, midrange and microcomputer systems. It uses two-dimensional rows and

columns to store data. The tables of records can be connected by common key values.

While working for IBM, E.F. Codd designed this structure in 1970. The model is not easy

for the end user to run queries with because it may require a complex combination of

many tables.




The multidimensional structure




       The multidimensional structure is similar to the relational model. The dimensions

of the cube-like model have data relating to elements in each cell. This structure gives a

spreadsheet-like view of data. This structure is easy to maintain because records are

stored as fundamental attributes—in the same way they are viewed—and the structure is

easy to understand. Its high performance has made it the most popular database structure

when it comes to enabling online analytical processing (OLAP).




Eastwoods Professional College of Science and Technology                          Page 22
The object-oriented structure




       The object-oriented structure has the ability to handle graphics, pictures, voice

and text, types of data, without difficultly unlike the other database structures. This

structure is popular for multimedia Web-based applications. It was designed to work with

object-oriented programming languages such as Java.




       The dominant model in use today is the ad hoc one embedded in SQL,despite the

objections of purists who believe this model is a corruption of the relational model since

it violates several fundamental principles for the sake of practicality and performance.

Many DBMSs also support the Open Database Connectivity API that supports a standard

way for programmers to access the DBMS.




       Before the database management approach, organizations relied on file processing

systems to organize, store, and process data files. End users criticized file processing

because the data is stored in many different files and each organized in a different way.

Each file was specialized to be used with a specific application. File processing was

bulky, costly and nonflexible when it came to supplying needed data accurately and

promptly. Data redundancy is an issue with the file processing system because the

independent data files produce duplicate data so when updates were needed each separate

file would need to be updated. Another issue is the lack of data integration. The data is


Eastwoods Professional College of Science and Technology                          Page 23
dependent on other data to organize and store it. Lastly, there was not any consistency or

standardization of the data in a file processing system which makes maintenance difficult.

For these reasons, the database management approach was produced.




Data structure




       Data structures (fields, records, files and objects) optimized to deal with very

large amounts of data stored on a permanent data storage device (which implies relatively

slow access compared to volatile main memory).




Database query language

       A database query language and report object allows users to interactively

interrogate the database, analyze its data and update it according to the users privileges

on data. It also controls the security of the database. Data security prevents unauthorized

users from viewing or updating the database. Using passwords, users are allowed access

to the entire database or subsets of it called subschemas. For example, an employee

database can contain all the data about an individual employee, but one group of users

may be authorized to view only payroll data, while others are allowed access to only

work history and medical data.




Eastwoods Professional College of Science and Technology                           Page 24
       If the DBMS provides a way to interactively enter and update the database, as

well as interrogate it, this capability allows for managing personal databases. However, it

may not leave an audit trail of actions or provide the kinds of controls necessary in a

multi-user organization. These controls are only available when a set of application

programs are customized for each data entry and updating function.




Transaction mechanism




       A database transaction mechanism ideally guarantees ACID properties in order to

ensure data integrity despite concurrent user accesses (concurrency control), and faults

(fault tolerance). It also maintains the integrity of the data in the database. The DBMS

can maintain the integrity of the database by not allowing more than one user to update

the same record at the same time. The DBMS can help prevent duplicate records via

unique index constraints; for example, no two customers with the same customer

numbers (key fields) can be entered into the database. See ACID properties for more

information.




Eastwoods Professional College of Science and Technology                           Page 25
External, logical and internal view




                                    Traditional view of data


       A DBMS Provides the ability for many different users to share data and process

resources. As there can be many different users, there are many different database needs.

The question is: How can a single, unified database meet varying requirements of so

many users?


       A DBMS minimizes these problems by providing three views of the database

data: an external view (or user view), logical view (or conceptual view) and physical (or

internal) view. The user’s view of a database program represents data in a format that is

meaningful to a user and to the software programs that process those data.




Eastwoods Professional College of Science and Technology                         Page 26
          One strength of a DBMS is that while there is typically only one conceptual (or

logical) and physical (or internal) view of the data, there can be an endless number of

different external views. This feature allows users to see database information in a more

business-related way rather than from a technical, processing viewpoint. Thus the logical

view refers to the way the user views the data, and the physical view refers to the way the

data are physically stored and processed.




Features and capabilities




          Alternatively, and especially in connection with the relational model of database

management, the relation between attributes drawn from a specified set of domains can

be seen as being primary. For instance, the database might indicate that a car that was

originally "red" might fade to "pink" in time, provided it was of some particular "make"

with an inferior paint job. Such higher arity relationships provide information on all of

the underlying domains at the same time, with none of them being privileged above the

others.




Eastwoods Professional College of Science and Technology                           Page 27
Characteristics of Databases


       A computerized database refers to a collection of related files that are digitized.

More often than not, this kind of database is more useful than manila folders and filing

cabinets. For one, it provides an efficient method of pulling facts together. It allows the

slicing, dicing, mixing, and matching of information for a myriad of purposes and needs.




After reading this lesson, you should be able to:




      Identify some of the common types of databases.

      Discuss some of the key issues associated with providing data access.

      Justify the importance of maintaining separate files.

      Justify the importance of minimizing redundancy between data files.




Types of Databases


       Some databases are small enough to be created and contained on your desktop

computer while others are so large that they are stored on network servers or powerful

mainframe computers. Popular database management software applications such as

Paradox, Access, and dBASE 5 are utilized to manage databases small enough to be

stored on a desktop computer. Individuals use these programs to perform specific tasks,

such as to keep track of customers and manage data for small research projects.

Eastwoods Professional College of Science and Technology                           Page 28
Some databases are so large that that they must be stored on a server or mainframe

computer and accessed by going online. Some large, public databases can be accessed

online for a fee. These are referred to as information utilities or online services. You may

have heard of or used some of the more popular online services including America

Online, CompuServe, and Microsoft Network. These online services provide access to a

myriad of information sources concerning weather, news, travel, shopping, and a great

deal more. Even specialized public databases can be accessed online. Lexis, which gives

lawyers access to local, state, and federal laws, is just one example. There are many other

types of large databases. Many museums have put artwork online, creating virtual art

museums. Most university libraries have created electronic databases to compliment or

substitute for their card catalogues.




Database Access



       Database access is a sticky issue, as you will see. The following example

illustrates some of the difficulties that data administrators, organizations, and society in

general now face. A decade ago, Congress created a medical practitioner database to keep

physicians disciplined by the medical board of one state from avoiding detection if they

moved to another state and applied for a medical license. Should doctor databases be

opened to the public? If given access to the database, patients could look up information

about a specific doctor and find out if other patents have lodged complaints against them.



Eastwoods Professional College of Science and Technology                            Page 29
In one case, a women whose obstetrician left unsightly scars on her abdomen after

delivering her baby said if she had been allowed access to the database, she would have

learned of other patients' complaints and chosen another doctor. On the other hand, many

physicians complain that by making such data available, they are less likely to perform

high-risk procedures, even when it might be beneficial to the patient. Those doctors

performing high-risk procedures are more likely to receive complaints and could

potentially face disciplinary action. You can begin to see the challenges associated with

determining who should have access to certain types of information.




Database Attributes for Effective Use



It is important to keep some database files separate, even though they contain closely

related information. For example, it's usually a good idea to keep employee files

containing home address, telephone number, job title, and work location separate from

files containing an employee's tax and salary information. There are at least two reasons

for maintaining these records in separate files:




It is generally more efficient and effective to search for and extract information from

smaller sets of data. In other words, users can access data more rapidly by using smaller

files than by trying to access the same data in a large composite file containing vast

amounts and types of data. The more types of data contained in a database, the more

Eastwoods Professional College of Science and Technology                            Page 30
complex the database becomes and the more difficult it is for database management

systems to manipulate it accurately and efficiently.


Different types of data should be accessible to different groups of people. For example,

all employees may be given access to employee information such as work location, job

title, and home telephone number. Tax deduction and salary information might only be

made available to human resource personnel and the accounting department in an

organization. Different functional groups in an organization require access to different

types of data. This makes sense when you consider the need to maintain some degree of

security and personal privacy.




Multiple Sources



A database is more useful if there is little redundancy between the files it contains. In

other words, it would be inefficient and a waste of human and computer resources to have

the same information repeated over and over again in different files. Some companies

maintain databases with very similar information. Sometimes there are good reasons for

this; e.g. for security purposes. However, it's simply more costly to maintain accurate

information in multiple locations. In addition, there would also be a need to resolve

discrepancies occurring between the same information in multiple files.




Eastwoods Professional College of Science and Technology                         Page 31
One of the beauties of databases is the ability to link together data from multiple sources

to accomplish a specific task. For example, I might store the file containing a mailing list

for Pennsylvania with similar lists compiled for individuals in the other fifty states. If a

political action group in Pennsylvania decides to develop a campaign for the northeast

region, they can extract the names of potential supporters for the states of New York,

Connecticut, Maine, and other northeastern states.




Simple definition


        A database management system is the system in which related data is stored in an

efficient or compact manner. "Efficient" means that the data which is stored in the DBMS

can be accessed quickly and "compact" means that the data takes up very little space in

the computer's memory. The phrase "related data" means that the data stored pertains to a

particular topic.




        Specialized databases have existed for scientific, imaging, document storage and

like uses. Functionality drawn from such applications has begun appearing in mainstream

DBMS's as well. However, the main focus, at least when aimed at the commercial data

processing market, is still on descriptive attributes on repetitive record structures.




Eastwoods Professional College of Science and Technology                                 Page 32
       Thus, the DBMSs of today roll together frequently needed services and features

of attribute management. By externalizing such functionality to the DBMS, applications

effectively share code with each other and are relieved of much internal complexity.

Features commonly offered by database management systems include:




Query ability




       Querying is the process of requesting attribute information from various

perspectives and combinations of factors. Example: "How many 2-door cars in Texas are

green?" A database query language and report writer allow users to interactively

interrogate the database, analyze its data and update it according to the users privileges

on data.




Backup and replication




       Copies of attributes need to be made regularly in case primary disks or other

equipment fails. A periodic copy of attributes may also be created for a distant

organization that cannot readily access the original. DBMS usually provide utilities to

facilitate the process of extracting and disseminating attribute sets. When data is

replicated between database servers, so that the information remains consistent

Eastwoods Professional College of Science and Technology                          Page 33
throughout the database system and users cannot tell or even know which server in the

DBMS they are using, the system is said to exhibit replication transparency.




Rule enforcement




       Often one wants to apply rules to attributes so that the attributes are clean and

reliable. For example, we may have a rule that says each car can have only one engine

associated with it (identified by Engine Number). If somebody tries to associate a second

engine with a given car, we want the DBMS to deny such a request and display an error

message. However, with changes in the model specification such as, in this example,

hybrid gas-electric cars, rules may need to change. Ideally such rules should be able to be

added and removed as needed without significant data layout redesign.




Security




       For security reasons, it is desirable to limit who can see or change specific

attributes or groups of attributes. This may be managed directly on an individual basis, or

by the assignment of individuals and privileges to groups, or (in the most elaborate

models) through the assignment of individuals and groups to roles which are then granted

entitlements.

Eastwoods Professional College of Science and Technology                           Page 34
Computation




       Common computations requested on attributes are counting, summing, averaging,

sorting, grouping, cross-referencing, and so on. Rather than have each computer

application implement these from scratch, they can rely on the DBMS to supply such

calculations.




Change and access logging




       This describes who accessed which attributes, what was changed, and when it was

changed. Logging services allow this by keeping a record of access occurrences and

changes.




Automated optimization

       For frequently occurring usage patterns or requests, some DBMS can adjust

themselves to improve the speed of those interactions. In some cases the DBMS will

merely provide tools to monitor performance, allowing a human expert to make the

necessary adjustments after reviewing the statistics collected.




Eastwoods Professional College of Science and Technology                      Page 35
Meta-data repository




       Metadata is data describing data. For example, a listing that describes what

attributes are allowed to be in data sets is called "meta-information".




Advanced DBMS




   An example of an advanced DBMS is Distributed Data Base Management System

(DDBMS), a collection of data which logically belong to the same system but are spread

out over the sites of the computer network. The two aspects of a distributed database are

distribution and logical correlation:




      Distribution: The fact that the data are not resident at the same site, so that we can

       distinguish a distributed database from a single, centralized database.




      Logical Correlation: The fact that the data have some properties which tie them

       together, so that we can distinguish a distributed database from a set of local

       databases or files which are resident at different sites of a computer network.




Eastwoods Professional College of Science and Technology                             Page 36
Types of database engines

Embedded database

An embedded database system is a database management system (DBMS) which is

tightly integrated with an application software that requires access to stored data, such

that the database system is “hidden” from the application’s end-user and requires little or

no ongoing maintenance. It is actually a broad technology category that includes database

systems with differing application programming interfaces (SQL as well as proprietary,

native APIs); database architectures (client/server and in-process); storage modes (on-

disk, in-memory and combined); database models (relational, object-oriented, Entity-

Attribute-Value model and network/CODASYL); and target markets. The term

"embedded database" can be confusing because only a small subset of embedded

database products is used in real-time embedded systems such as telecommunications

switches and consumer electronics devices.




In-memory database

An in-memory database (IMDB; also main memory database system or MMDB) is a

database management system that primarily relies on main memory for computer data

storage. It is contrasted with database management systems which employ a disk storage

mechanism. Main memory databases are faster than disk-optimized databases since the

internal optimization algorithms are simpler and execute fewer CPU instructions.

Accessing data in memory reduces the I/O reading activity when querying the data which


Eastwoods Professional College of Science and Technology                           Page 37
provides faster and more predictable performance than disk. In applications where

response time is critical, such as telecommunications network equipment and mobile ads

networks, main memory databases are often used.




The Value of Data and Databases




Many of the actions you make during the day become data for organizations to use for

their own profit and learning. Using an automated teller machine, filling out a form for a

driver's license, ordering a book on the Internet, booking a flight on an airline - all

become digitized data to be sorted, managed, and used by others. In each of these cases,

someone at some time has decided how the data from these users will be received, stored,

processed, and made available to others.




After reading this lesson, you should be able to:


      Describe the value of data to organizations.

      Discuss how and why organizations and individuals attempt to extract meaning

       from data.

      Data and Organizations




Eastwoods Professional College of Science and Technology                          Page 38
For financial and/or legal reasons, organizations collect and store vast amounts of data

about employees, customers, finances, vendors, inventory, competitors, and markets, to

name only a few. The amount of data needed is important because people generally make

better decisions if they have more data available to them.




For example, a car dealership, bank, or credit union will make better decisions about who

to give car loans by looking at a person's credit report information than if they simply

based their decision on the word of the customer. Looking at your credit report, a bank

representative would see a listing of your payment history on loans and credit cards,

including your mortgage. She would also see information about outstanding loans, debt

repayment and credit limits. The report may also contain information about jobs you have

held and public record information (birth date and address).




Likewise, a factory will improve its ability to manufacture products by tracking and

managing data about inventory (name, identification number, location, and quantity),

production schedule, quality control measures, and much more. You can begin to see why

collecting data is important. However, the true value of data cannot be realized until it is

appropriately organized, stored, analyzed, and eventually used for a specific purpose.




Eastwoods Professional College of Science and Technology                            Page 39
Extracting Meaning from Data




Raw data is not very useful. Suppose a human resources manager of a local hospital

sends out a survey consisting of 25 multiple-choice questions to assess the level of

employee satisfaction of its 150 nurses. Let's assume for a moment that 114 surveys are

completed and returned to the manager. This is the raw data and basically has no

meaning.




As a next step, the responses of each nurse to each question on the survey are entered and

stored in a computer. The data is still raw and meaningless. It becomes more organized if

it is entered into a computer with a plan and purpose in mind. If the manager is smart, he

will assign each a nurse an ID number and enter all of his or her responses, not at

random, but in the order in which they appear in the survey.




Ultimately, the data cannot be understood until it is analyzed. This can be accomplished

by calculating the average score for each nurse, the average score for all the nurses at the

hospital, the average score for the nurses in each department, and so on. As the manager

begins to process and analyze the data, it eventually begins to tell a story. Hopefully, the

story will increase understanding in a way that enables the manager to improve the level

of satisfaction of the group of employees.




Eastwoods Professional College of Science and Technology                            Page 40
Understanding Database Terminology




A computer cannot process data unless it is organized in special ways; into characters,

fields, records, files and databases.


After reading this lesson, you should be able to:




      Define the key terms needed to understand what a database is and how it is used.

      Identify the purpose and role of characters in data processing.

      Identify the purpose and role of fields in data processing.

      Identify the purpose and role of records in data processing.

      Identify the purpose and role of database files in data processing.

      Identify the purpose and role of databases in data processing.

      Identify the purpose and role of data management systems in data processing.

      Identify the purpose and role of keys in data processing.




Character




A character is the most basic element of data that can be observed and manipulated.

Behind it are the invisible data elements we call bits and bytes, referring to physical



Eastwoods Professional College of Science and Technology                         Page 41
storage elements used by the computer hardware. A character is a single symbol such as a

digit, letter, or other special character (e.g., $, #, and ?).




Field




        A field contains an item of data; that is, a character, or group of characters that are

related. For instance, a grouping of related text characters such as "John Smith" makes up

a name in the name field. Let's look at another example. Suppose a political action group

advocating gun control in Pennsylvania is compiling the names and addresses of potential

supporters for their new mailing list. For each person, they must identify the name,

address, city, state, zip code and telephone number. A field would be established for each

type of information in the list. The name field would contain all of the letters of the first

and last name. The zip code field would hold all of the digits of a person's zip code, and

so on. In summary, a field may contain an attribute (e.g., employee salary) or the name of

an entity (e.g., person, place, or event).




Eastwoods Professional College of Science and Technology                              Page 42
Record




       A record is composed of a group of related fields. As another way of saying it, a

record contains a collection of attributes related to an entity such as a person or product.

Looking at the list of potential gun control supporters, the name, address, zip code and

telephone number of a single individual would constitute a record. A payroll record

would contain the name, address, social security number, and title of each employee.




Eastwoods Professional College of Science and Technology                            Page 43
Database File




       As we move up the ladder, a database file is defined as a collection of related

records. A database file is sometimes called a table. A file may be composed of a

complete list of individuals on a mailing list, including their addresses and telephone

numbers. Files are frequently categorized by the purpose or application for which they

are intended. Some common examples include mailing lists, quality control files,

inventory files, or document files. Files may also be classified by the degree of

permanence they have. Transition files are only temporary, while master files are much

more long-lived.




Eastwoods Professional College of Science and Technology                       Page 44
Database


Organizations and individuals use databases to bring independent sources of data together

and store them electronically. Thus, a database is composed of related files that are

consolidated, organized and stored together. One collection of related files might pertain

to employee information. Another collection of related files might contain sports

statistics.


Organizations and individuals may have and use many different databases, depending on

the nature of the work involved. For example, a library database might consist of several

related, but separate, databases including book titles and author names, book description,

books on order, books checked out, and similar sets of information. Most organizations

have product information databases, customer databases, and human resource databases

that contain information about employees, salaries, home address, stock purchase plans,

and tax deduction information. In each case, the data stored in a database is independent

from the application programs which use and process the data.




Eastwoods Professional College of Science and Technology                          Page 45
Data Management System


Data management systems are used to access and manipulate data in a database. A

database management system is a software package that enables users to edit, link, and

update files as needs dictate. Database management systems will be discussed in greater

detail in another lesson.


Key




       In order to track and analyze data effectively, each record requires a unique

identifier or what is called a key. The key must be completely unique to a particular

record just as each individual has a unique social security number assigned to them. In

fact, social security numbers are often used as keys in large databases. You might think

that the name field would be a good choice for a key in a mailing list. However, this

would not be a good choice because some people might have the same name. A key must

be identified or assigned to each record for computerized information processing to

function correctly. An existing field may be used if the entries are entirely unique, such

as a social security or telephone number. In most cases, a new field will be developed to

hold a key, such as a customer number or product number.


Eastwoods Professional College of Science and Technology                            Page 46
                                    Conclusion




        As you can see, from learning about the database system much of what we have

discussed can be very useful in applying it to our everyday lives. The database

management system can be a very useful asset in the business world or in the lives of

people every day. Furthermore because it has the ability to increase networking and

mobility, the database system will be a great benefit for communication methods among

the different businesses. After learning about the database management, it would be of

great assistance when people become more aware of what they are using in the business

or in their everyday life.




Eastwoods Professional College of Science and Technology                      Page 47
                                   Bibliography



^ Codd, E.F. (1970)."A Relational Model of Data for Large Shared Data Banks". In:

Communications of the ACM 13 (6): 377–387.


^ "A set theoretic data structure and retrieval language" (PDF), William R. Hershey and

Carol H. Easthope, Paper from the Session on Data Structures, Spring Joint Computer

Conference, May 1972 in ACM SIGIR Forum, Volume 7, Issue 4 (December 1972), pp.

45-55, DOI=10.1145/1095495.1095500


^ "Sets, Data Models and Data Independence", by Ken North a Dr. Dobb's Blogger,

March 10, 2010


^ Description of a set-theoretic data structure, D. L. Childs, 1968, Technical Report 3 of

the CONCOMP (Research in Conversational Use of Computers) Project, University of

Michigan, Ann Arbor, Michigan, USA


^ Feasibility of a Set-Theoretic Data Structure : A General Structure Based on a

Reconstituted Definition of Relation, D. L. Childs, 1968, Technical Report 6 of the

CONCOMP (Research in Conversational Use of Computers) Project, University of

Michigan, Ann Arbor, Michigan, USA


^ MICRO Information Management System (Version 5.0) Reference Manual, M.A.

Kahn, D.L. Rumelhart, and B.L. Bronson, October 1977, Institute of Labor and Industrial

Relations (ILIR), University of Michigan and Wayne State University




Eastwoods Professional College of Science and Technology                          Page 48
^ Development of an object-oriented DBMS; Portland, Oregon, United States; Pages: 472

– 482; 1986; ISBN 0-89791-204-7


^ Performance enhancement through replication in an object-oriented DBMS; Pages 325–

336; ISBN 0-89791-317-5


^ Seltzer, M. (2008, July). Beyond Relational Databases. Communications of the ACM,

51(7), 52–58. Retrieved July 6, 2009, from Business Source Complete database.


^ itl.nist.gov (1993) Integration Definition for Information Modeling (IDEFIX). 21

December 1993.


Website: http://en.wikipedia.org/wiki/Database_management_system




Eastwoods Professional College of Science and Technology                        Page 49

				
DOCUMENT INFO
Shared By:
Categories:
Tags:
Stats:
views:12
posted:4/16/2012
language:English
pages:49