3 Chapter 03 Database DBMS

Chapter -03

Database and

Database Management Systems (DBMS)

Source: Haag, Stephan et. el. (2006). Business Driven Technology, New York: McGraw-Hil. P. 75

Management Information Systems Page 31

Chapter-3 Database and DBMS

3.1 Introduction to Database

A database is an organized collection of data. The data are typically organized to model relevant aspects of reality in a way that supports processes requiring this information. For example, modeling the availability of rooms in hotels in a way that supports finding a hotel with vacancies. A database is defined as a structured set of data held in a computer. This data is usually made accessible to all who will need the data in some way. Databases are important to businesses because they allow for important information to be updated, shared, deleted, retrieved, and added within seconds. This makes things more efficient and less costly for the business.

This chapter provides Database and Database Management System (DBMS) which is a set of

programs that enables a person to store, modify, and extract information from a database. It also

provides users with tools to add, delete, access, modify, and analyze data stored in one location.

A group can access the data by using query and reporting tools that are part of the DBMS or by

using application programs specifically written to access the data. DBMS also provides the

method for maintaining the integrity of stored data, running security and users access, and recovering information if the system fails. The information from a database can be presented in a

variety of formats. Most DBMSs include a report writer program that enables us to present data

in the form of a report. Many DBMSs also contain a graphics component that enables one to

output information in the form of table, graphs and charts.

3.2 Define database. Write importance of database in business.

A database is an integrated collection of logically related data elements. A database consolidates records previously stored in separate files into a common pool of data elements that provides data for many applications. The data stored in a database are independent of the application programs using them and of the type of storage devices on which they are stored.1

A database is a collection of related files. It is also defined as a group of stored, integrated (cross-referenced) data elements that can be retrieved and manipulated with great flexibility to

produce information.2 It is a large collection of stored, integrated records that can be

maintained and manipulated with great flexibility; the top level in the data hierarchy.

A database is a structured collection of data. The data is typically organized to model relevant aspects of reality (for example, the availability of rooms in hotels), in a way that supports processes requiring this information (for example, finding a hotel with vacancies).

A database management system (DBMS) is a computer program (or more typically, a suite of them) designed to manage a database, a large set of structured data, and run operations on the data requested by numerous users. Typical examples of DBMS use include accounting, human resources and customer support systems.



A database management system (or DBMS) is essentially nothing more than a computerized data-keeping system. Users of the system are given facilities to perform several kinds of operations on such a system for either manipulation of the data in the database or the management of the database structure itself. Database Management Systems (DBMSs) are categorized according to their data structures or types.

Figure: 3.1 http://en.wikipedia.org/wiki/Database_management_system

The term database is correctly applied to the data and their supporting data structures, and not to the database management system (DBMS). The database data collection with DBMS is called

a database system.3 The term database system implies that the data is managed to some level

of quality (measured in terms of accuracy, availability, usability, and resilience) and this in turn often implies the use of a general-purpose database management system (DBMS). A general-purpose DBMS is typically a complex software system that meets many usage requirements to

properly maintain its databases which are often large and complex.4

3.3 Database Terminology



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

records, files and databases.

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 storage elements used by

the computer hardware. A character is a single symbol such as a digit, letter, or other special

character (like A, B,C, $, #,? etc.).

Field



Figure: 3.1-(A) http://en.wikipedia.org/wiki/Database_management_system

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., Name, designation, Basic, person,

place, or event).

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.

Figure: 3.1-(B) http://en.wikipedia.org/wiki/Database_management_system

Database File



Figure: 3.1-(C) http://en.wikipedia.org/wiki/Database_management_system

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.

Database

A database is an integrated collection of logically related data elements. A database consolidates

records previously stored in separate files into a common pool of data elements that provides

data for many applications.

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.

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 elsewhere.



Key field

Figure: 3.1-(D) http://en.wikipedia.org/wiki/Database_management_system

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. One 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.

A Database system ensures that an appropriate data is collected from the various sources,

processed, and sent further to all the needy destinations. The system is expected to fulfill the

information needs of an individual, a group of individuals, the management functionaries: the

managers and the top management. Managing is necessary whenever one needs to get thing

done. It may be called the practices of consciously and continually shaping organizations. Each

and every organization has people who are entrusted with the responsibility of helping the

organization achieve its goals. Those people are called managers. No organization can carry on

its business without management, which is in turn supervised by managers.



Figure 3.2 http://blog.maia-intelligence.com/2008/04/26/functional-management-information-system-mis/

A database contains a collection of related items or facts arranged in a specific structure.5 The most obvious example of a non-computerized database is a telephone directory. Telephone companies use electronic database programs to produce their printed phone books.

A way to classify databases involves the type of their contents, for example: bibliographic, document-text, statistical, or multimedia objects. Another way is by their application area, for

example: accounting, music compositions, movies, banking, manufacturing, or insurance.6

The term database may be narrowed to specify particular aspects of organized collection of data and may refer to the logical database, to the physical database as data content in computer data storage or to many other database sub-definitions.

Figure 3.3 http://en.wikipedia.org/wiki/Computer_data_storage

This document describes how Web services based on the use of XML/SOAP can be used to

provide Data Base facilities for a range of Data Acquisition Applications.

The server is normally an Http task which contains software to implement the Data Base

functions. The user interacts either via a Web Browser which uses Html and JavaScript to



communicate with client software within the Http task or via a GUI Client Application which

uses SOAP messages to communicate directly with the Data Base software.

Database

Figure 3.4 http://ecommercecenter.net/management/what-is-a-data-warehouse.html

3.4 What is Database Management System (DBMS)? Write importance of DBMS.

A Database Management System (DBMS) is a set of programs that enables management to store,

modify, and extract information from a database, it also provides users with tools to add, delete,

access, modify, and analyze data stored in one location. A group can access the data by using

query and reporting tools that are part of the DBMS or by using application programs

specifically written to access the data. DBMSs also provide the method for maintaining the integrity of stored data, running security and users access, and recovering information if the

system fails. The information from a database can be presented in a variety of formats. Most

DBMSs include a report writer program that enables one to output data in the form of a report.

Many DBMSs also include a graphics component that enables you to output information in the

form of graphs and charts.7

Well known DBMSs include Oracle, Sybase, FoxPro, IBM DB2, Linter, Microsoft Access, Microsoft SQL Server, MySQL, Postgre SQL and SQLite. A database is not generally portable across different DBMS, but different DBMSs can inter-operate to some degree by using standards like SQL and ODBC together to support a single application built over more than one database. A DBMS also needs to provide effective run-time execution to properly support (e.g., in terms of performance, availability, and security) as many database end-users as needed.8

A Database Management System (DBMS) is software through which users application programs

interact with a database. The users sends requests to the DBMS and the DBMS performs the

actual manipulation of the information in the database. 9 The user sends requests to the DBMS

and the DBMS performs the actual manipulation of the information in the database. There are

two primary ways that users can interact with a DBMS: (1) Directly and (2) indirectly.10



Figure http://www.google.com/imgres?q=database+management+systems&um=1&hl =1

Database Management System is a software package that has been designed to create and maintain shared collection of logically related data. It generally facilitates the processes of Defining, Constructing and Manipulating of data. In addition to that it provides various background services including transaction management, disaster recovery and security. Data management has become a high priority issue in modern business management. Therefore to support that, database management systems providers improving their products using innovative technologies.

Figure 3.5 http://en.wikipedia.org/wiki/Database

Database and database management system are essential to all areas of business, and they must

be carefully managed. There are many different types of DBMSs, ranging from small systems

that run on personal computers to huge systems that run on mainframes. The following are

examples of database applications: computerized library systems, flight reservation systems, and

computerized parts inventory systems. 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.11



Figure 3.6 http://entrance-exam.net/forum/general-discussion/difference-between-dbms-rdbms-349253.html

Database Management Systems (DBMS) is simply the software that permits an organization to

centralize data, manage them efficiently, and provide access to the stored data by application

program. DBMS is special software to create and maintain a database and enable individual

business applications to extract the data they need without having to create separate files or data

definitions in their computer programs.12

Database Management System Software that controls the organization, storage, retrieval,

security and integrity of data in a database. It accepts requests from the application and instructs

the operating system to transfer the appropriate data. The major DBMS vendors are Oracle, IBM,

Microsoft and Sybase (see Oracle database, DB2, SQL Server and ASE). MySQL is a very

popular open source product ( MySQL). DBMSs may work with traditional programming

languages (COBOL, C, etc.) or they may include their own programming language for

application development. DBMSs let information systems be changed more easily as the

organization's requirements change. New categories of data can be added to the database without

disruption to the existing system. Adding a field to a record does not require changing any of the

programs that do not use the data in that new field.13

3.5 What is Relational Database Management System (RDBMS)? Write importance of

RDBMS in IT and business.

There are many different models for organizing information in a database, including the hierarchical database, network database, and the most prevalent-the relational database model. Broadly defined, a database maintains information about various types of objects, events, people, and places. The hierarchical database stores related information in terms of predefined categorical relationships in a tree-like fashion. The network database is used by a network installation tool to allocate and track network resources. The relational database model is a type of database that stores its information in the form of logically related two-dimensional tables.



Figure 3.7 http://entrance-exam.net/forum/general-discussion/difference-between-dbms-rdbms-349253.html

3.5-(a) Write advantages of Relational Database

From a business perspective, database information offers many advantages, including:14

Increased flexibility

Increased scalability and performance

Reduced information redundancy

Increased information integrity Increased information security

DBMS is a collective measure which enables creation, modification to be carried out in

Database. DBMS can be carried out with various models like Relational model, Object model,

hierarchical and so on. Relational model of carrying out the database is known as RDBMS

(Relational Database Management System). The reason behind following RDBMS model for

database management is it as many advantages which are as follows.

3.6 What are the components of DBMS? Explain.



A Database Management System (DBMS) is a set of computer programs that controls the

creation, maintenance, and the use of a database. It allows organizations to place control of

database development in the hands of database administrators (DBA) and other specialists.

Components of DBMS

1) DBMS Engine accepts logical request from the various other DBMS subsystems,

converts them into physical equivalents, and actually accesses the database and data

dictionary as they exist on a storage device.

2) Data Definition Subsystem helps user to create and maintain the data dictionary and

define the structure of the files in a database.

3) Data Manipulation Subsystem helps 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 user to specify its logical information

requirements.

4) Application Generation Subsystem contains facilities to help users to develop

transaction-intensive applications. It usually requires that user perform a detailed series of

tasks to process a transaction. It facilitates easy-to-use data entry screens, programming

languages, and interfaces.

5) Data Administration Subsystem helps users to manage the overall database

environment by providing facilities for backup and recovery, security management, query

optimization, concurrency control, and change management.



3.7 Define Data Warehouse. Write benefits of Warehouse in modern ICT.

A data warehouse is a place where data is stored for archival purposes, analysis purposes and security purposes. Usually a data warehouse is either a single computer or many computers (servers) tied together to create one giant computer system.

Data can consist of raw data or formatted data and can be on various types of topics including an organizations sales, salaries, operational data, summaries of data including reports, copies of data, human resource data, inventory data, external data to provide simulations and analysis, etc.

Besides being a store house for large amounts of data, they must possess systems in place that make it easy to access the data and use it in day to day operations. A data warehouse is sometimes said to be a major part in a decision support system. A way for an organization to use data to come up with facts, trends or relationships that can help them make effective decisions or create effective strategies to accomplish their goals.

Figure 3.8-(A)http://www.google.com/imgres?q=database+management+systems&um=1&hl



Figure 3.8-(B) http://ecommercecenter.net/management/what-is-a-data-warehouse.html

There are many different models of data warehouses including Online Transaction Processing which is a warehouse built for speed and ease of use. Another type of data warehouse is called Online Analytical processing, this type of warehouse is more difficult to use and adds an extra step of analysis within the data. Usually it requires more steps which slows the process down and much more data in order to analyze certain queries.

A Data Warehouse is logical collection of information- gathered from many different operational databases-that supports business analysis activities and decision-making tasks. The primary purpose of a data warehouse is to aggregate information throughout an organization into a single repository in such a way that employees can make decisions and undertake business analysis activities. 15 Therefore, while database store the details of all transaction (for instance, the sale of a product) and events (hiring a new employee), data warehouses store that same information but in an aggregated from more suited to supporting decision making tasks. Aggregation, in this instance, can include totals, counts, averages, and the like because of this sort of aggregation, data warehouse support online analytical processing or OLTP.16

Figure 3.9 Haag, Stephan et. el. (2006). Business Driven Technology, New York: McGraw-Hill. P. 75

The data warehouse modeled in above Figure 4.10 compile information from internal database and external database through extraction, transformation, and loading (ETL), which is a process that extracts information from internal and external database, transforms the information using a common set of enterprise definitions, and loads the information into a data warehouse. The data warehouse then sends subsets of the information to data marts. A data mart contains a subset of data warehouse information. To distinguish between data warehouse and data marts, thin of data warehouses as having a more organizational focus and data marts having focused information subsets particular to needs of a given business unit such as finance or production and operations.



Figure 3.11 http://ebiz-wiki.com/index.php/Data_Warehouse_vs_Operational_Database

A Data Warehouse is a corporate database that is characterized by integration and debugs information from one or more different sources, and then allowing it to process analysis from many points of view and high speed of response. The creation of a data warehouse represents in most cases the first step, from the technical point of view, to implement comprehensive and reliable business intelligence.

3.8 What is Data Mining?

Data mining is the practice of automatically searching large stores of data to discover patterns and trends that go beyond simple analysis. Data mining uses sophisticated mathematical algorithms to segment the data and evaluate the probability of future events. Data mining is also known as Knowledge Discovery in Data (KDD).

The key properties of data mining are:

Automatic discovery of patterns Prediction of likely outcomes Creation of actionable information Focus on large data sets and databases

Data mining can answer questions that cannot be addressed through simple query and reporting techniques.



Automatic Discovery

Data mining is accomplished by building models. A model uses an algorithm to act on a set of data. The notion of automatic discovery refers to the execution of data mining models.

Data mining models can be used to mine the data on which they are built, but most types of models are generalizable to new data. The process of applying a model to new data is known as scoring. Oracle Data Mining Application Developer's Guide for a discussion of scoring and deployment in Oracle Data Mining.

Prediction

Many forms of data mining are predictive. For example, a model might predict income based on education and other demographic factors. Predictions have an associated probability (How likely is this prediction to be true?). Prediction probabilities are also known as confidence (How confident can I be of this prediction?).

Some forms of predictive data mining generate rules, which are conditions that imply a given outcome. For example, a rule might specify that a person who has a bachelor's degree and lives in a certain neighborhood is likely to have an income greater than the regional average. Rules have an associated support (What percentage of the population satisfies the rule?).

Grouping

Other forms of data mining identify natural groupings in the data. For example, a model might identify the segment of the population that has an income within a specified range, that has a good driving record, and that leases a new car on a yearly basis.

Actionable Information

Data mining can derive actionable information from large volumes of data. For example, a town planner might use a model that predicts income based on demographics to develop a plan for low-income housing. A car leasing agency might a use model that identifies customer segments to design a promotion targeting high-value customers.

Data Mining and Statistics

There is a great deal of overlap between data mining and statistics. In fact most of the techniques used in data mining can be placed in a statistical framework. However, data mining techniques are not the same as traditional statistical techniques.

Traditional statistical methods, in general, require a great deal of user interaction in order to validate the correctness of a model. As a result, statistical methods can be difficult to automate.



Moreover, statistical methods typically do not scale well to very large data sets. Statistical methods rely on testing hypotheses or finding correlations based on smaller, representative samples of a larger population.

Data mining methods are suitable for large data sets and can be more readily automated. In fact, data mining algorithms often require large data sets for the creation of quality models.

Data Mining and OLAP

On-Line Analytical Processing (OLAP) can been defined as fast analysis of shared multidimensional data. OLAP and data mining are different but complementary activities.

OLAP supports activities such as data summarization, cost allocation, time series analysis, and what-if analysis. However, most OLAP systems do not have inductive inference capabilities beyond the support for time-series forecast. Inductive inference, the process of reaching a general conclusion from specific examples, is a characteristic of data mining. Inductive inference is also known as computational learning.

OLAP systems provide a multidimensional view of the data, including full support for hierarchies. This view of the data is a natural way to analyze businesses and organizations. Data mining, on the other hand, usually does not have a concept of dimensions and hierarchies.

Data mining and OLAP can be integrated in a number of ways. For example, data mining can be used to select the dimensions for a cube, create new values for a dimension, or create new measures for a cube. OLAP can be used to analyze data mining results at different levels of granularity.

Data Mining can help you construct more interesting and useful cubes. For example, the results of predictive data mining could be added as custom measures to a cube. Such measures might provide information such as "likely to default" or "likely to buy" for each customer. OLAP processing could then aggregate and summarize the probabilities.

Data Mining and Data Warehousing

Data can be mined whether it is stored in flat files, spreadsheets, database tables, or some other storage format. The important criterion for the data is not the storage format, but its applicability to the problem to be solved.

Proper data cleansing and preparation are very important for data mining, and a data warehouse can facilitate these activities. However, a data warehouse will be of no use if it does not contain the data you need to solve your problem.



Oracle Data Mining requires that the data be presented as a case table in single-record case format. All the data for each record (case) must be contained within a row. Most typically, the case table is a view that presents the data in the required format for mining.

Over the years, many large organizations have accumulated massive amounts of data about their

customers, suppliers, products, and services. Even many new Web-based companies have

amassed large databases about people and products as they have grown. The WWW is itself a

large distributed data repository with untold potential. With the growing realization that these

vast data resources can be tapped for significant commercial gain, interest in data mining, data

warehousing, and data marts has virtually exploded.

After reading this lesson, you should be able to:

Compare data mining, data warehousing, and data marts.

Describe the purpose and value of data mining.

Describe the purpose and value of data warehousing.

Describe the purpose and value of data marts.

Data Mining

Data mining, also known as "knowledge discovery," refers to computer-assisted tools and

techniques for sifting through and analyzing these vast data stores in order to find trends,

patterns, and correlations that can guide decision making and increase understanding. Data

mining covers a wide variety of uses, from analyzing customer purchases to discovering

galaxies. In essence, data mining is the equivalent of finding gold nuggets in a mountain of data.

The monumental task of finding hidden gold depends heavily upon the power of computers.

Applications of Data Mining

Data mining includes a variety of interesting applications. A few examples are listed below:

1) By recording the activity of shoppers in an online store, such as Amazon.com, over time,

retailers can use knowledge of these patterns to improve the placement of items in the

layout of a mail-order catalog page or Web page.

2) Telephone companies mine customer billing data to identify customers who spend

considerably more than average on their monthly phone bill. The company can then

target these customers to sell additional services.

3) Marketers can effectively target the wants and needs of specific consumer groups by

analyzing data about customer preferences and buying patterns.

4) Hospitals use data mining to identify groups of people whose healthcare costs are likely

to increase in the near future so that preventative steps can be taken.



3.9 Write different features of a DBMS.

Data Security

The DBMS can prevent unauthorized users from viewing or updating the database. Using passwords,

users are allowed access to the entire database or a subset of it known as a "subschema." For example,

in an employee database, some users may be able to view salaries while others may view only work

history and medical data.17

Data Integrity

The DBMS can ensure that no more than one user can update the same record at the same time. It can keep duplicate records out of the database; for example, no two customers with the same customer number can be entered.

Interactive Query A DBMS provides a query language and report writer that lets users interactively interrogate the database. These essential components give users access to all management information as needed. See query language and report writer.

Database Design

A business information system is made up of subjects (customers, employees, vendors, etc.) and activities (orders, payments, purchases, etc.). Database design is the process of organizing this data into related record types. The DBMS that is chosen is the one that can support the organization's data structure while efficiently processing the transaction volume. Organizations may use one kind of DBMS for daily transaction processing and then move the detail to another DBMS better suited for random inquiries and analysis. Overall systems design decisions are performed by data administrators and systems analysts. Detailed database design is performed by database administrators.

3.10 Write different type of Databases.

There different types of Database in used:

1. Analytic Databases

An analytic database is a type of database built to store, manage and consume big data. It is designed to be used specifically with business analytics, big data and business intelligence (BI) solutions. An analytic database stores business, market or project data used in business analysis, projections and forecasting processes.



Analytic databases (Online Analytical Processing-OLAP) are primarily static, read-only store sales records over the last ten years in an analytic database and use that database to analyze marketing strategies in relationship to demographics.

On the web, you will often see analytic databases in the form of inventory catalogs such as the one shown previously from Amazon.com. An inventory catalog analytical database usually holds descriptive information about all available products in the inventory.

Web pages are generated dynamically by querying the list of available products in the inventory against some search parameters. The dynamically-generated page will display the information about each item (such as title, author, ISBN) which is stored in the database.

2. Operational Databases

An operational database stores information about the activities of an organization, for example customer relationship management transactions, in a computer database. Operational databases can be known as production database, especially when distinguishing from a "test database" or "development database" used by programmers. Operational databases allow a business to enter, gather, and retrieve large quantities of specific information, such as training status, personal employee information, sales, customer complaints, and previous proposal information. Storing information in a centralized area can increase retrieval time for users. An important feature of storing information in an operational database is the ability to share information across the company. Operational databases can be used to monitor activities, to audit suspicious transactions, or to review the history of dealings with a particular customer. They can also be part of the actual process of making and fulfilling a purchase, for example in e-commerce.

Operational databases (OLTP Online Transaction Processing), on the other hand, are used to manage more dynamic bits of data. These types of databases allow you to do more than simply view archived data. Operational databases allow you to modify that data (add, change or delete data).

These types of databases are usually used to track real-time information. For example, a company might have an operational database used to track warehouse/stock quantities. As customers order products from an online web store, an operational database can be used to keep track of how many items have been sold and when the company will need to reorder stock.

These databases store detailed data about the operations of an organization. They are typically

organized by subject matter, process relatively high volumes of updates using transactions.

Essentially every major organization on earth uses such databases. Examples include customer

databases that record contact, credit, and demographic information about a business' customers,

personnel databases that hold information such as salary, benefits, skills data about employees,



Enterprise resource planning that record details about product components, parts inventory, and

financial databases that keep track of the organization's money, accounting and financial

dealings.

3. Hierarchical Databases

As its name implies, the Hierarchical Database Model defines hierarchically-arranged data. Perhaps the most intuitive way to visualize this type of relationship is by visualizing an upside down tree of data. In this tree, a single table acts as the "root" of the database from which other tables "branch" out.

You will be instantly familiar with this relationship because that is how all windows-based directory management systems (like Windows Explorer) work these days. Relationships in such a system are thought of in terms of children and parents such that a child may only have one parent but a parent can have multiple children. Parents and children are tied together by links called "pointers" (perhaps physical addresses inside the file system). A parent will have a list of pointers to each of their children.

4. Distributed database

A distributed database is a database in which storage devices are not all attached to a common

processing unit such as the CPU, controlled by a distributed database management system

(together sometimes called a distributed database system). It may be stored in multiple

computers, located in the same physical location; or may be dispersed over a network of

interconnected computers. Unlike parallel systems, in which the processors are tightly coupled

and constitute a single database system, a distributed database system consists of loosely-coupled

sites that share no physical components.

System administrators can distribute collections of data (e.g. in a database) across multiple

physical locations. A distributed database can reside on network servers on the Internet, on

corporate intranets or extranets, or on other company networks. Because they store data across

multiple computers, distributed databases can improve performance at end-user worksites by

allowing transactions to be processed on many machines, instead of being limited to one.



Two processes ensure that the distributed databases remain up-to-date and current: replication and duplication.

1. Replication involves using specialized software that looks for changes in the distributive database. Once the changes have been identified, the replication process makes all the databases look the same. The replication process can be complex and time-consuming depending on the size and number of the distributed databases. This process can also require a lot of time and computer resources.

2. Duplication, on the other hand, has less complexity. It basically identifies one database as a master and then duplicates that database. The duplication process is normally done at a set time after hours. This is to ensure that each distributed location has the same data. In the duplication process, users may change only the master database. This ensures that local data will not be overwritten.

Both replication and duplication can keep the data current in all distributive locations.

Besides distributed database replication and fragmentation, there are many other distributed database design technologies. For example, local autonomy, synchronous and asynchronous distributed database technologies. These technologies' implementation can and does depend on the needs of the business and the sensitivity/confidentiality of the data stored in the database, and hence the price the business is willing to spend on ensuring data security, consistency and integrity.

When discussing access to distributed databases, Microsoft favors the term distributed query, which it defines in protocol-specific manner as "[a]ny SELECT, INSERT, UPDATE, or DELETE statement that references tables and row sets from one or more external OLE DB data sources". Oracle provides a more language-centric view in which distributed queries and distributed transactions form part of distributed SQL.

A distributed database system allows applications to access data from local and remote

databases. In a homogenous distributed database system, each database is an Oracle database. In

a heterogeneous distributed database system, at least one of the databases is a non-Oracle

database. Distributed databases use client/server architecture to process information requests.

The definition of a distributed database is broad, and may be utilized in different meanings. In

general it typically refers to a modular DBMS architecture that allows distinct DBMS instances

to cooperate as a single DBMS over processes, computers, and sites, while managing a single

database distributed itself over multiple computers, and different sites.

Examples are databases of local work-groups and departments at regional offices, branch offices,

manufacturing plants and other work sites. These databases can include both segments shared by

multiple sites, and segments specific to one site and used only locally in that site.



5. External database

Access to a wealth of information from external database is available for a fee from commercial

online service, and with or without charge from many source on the Internet, especially the

WWW site. Websites provide an endless variety of hyperlink pages of multimedia documents in

hypermedia database for you to access.

6. Data warehouse

Data warehouses archive data from operational databases and often from external sources such

as market research firms. Often operational data undergoes transformation on its way into the

warehouse, getting summarized, anonymized, reclassified, etc. The warehouse becomes the

central source of data for use by managers and other end-users who may not have access to

operational data.

For example, sales data might be aggregated to weekly totals and converted from internal

product codes to use UPCs so that it can be compared with ACNielsen data. Some basic and

essential components of data warehousing include retrieving, analyzing, and mining data,

transforming, loading and managing data so as to make it available for further use.

Operations in a data warehouse are typically concerned with bulk data manipulation, and as such,

it is unusual and inefficient to target individual rows for update, insert or delete. Bulk native

loaders for input data and bulk SQL passes for aggregation are the norm.

6. Hypermedia databases

The World Wide Web can be thought of as a database, albeit one spread across millions of

independent computing systems. Web browsers "process" this data one page at a time, while web

crawlers and other software provide the equivalent of database indexes to support search and

other activities. In a Hypertext database, any word or a piece of text representing an object, e.g.,

another piece of text, an article, a picture, or a film, can be linked to that object. Hypertext

databases are particularly useful for organizing large amounts of disparate information. For

example they are useful for organizing online encyclopedias, where users can conveniently jump

in the texts, in a controlled way, by using hyperlinks.



Questions

1. Define Database Management Systems (DBMS).

2. What are the differences among Database, DBMS, RDBMS? Explain.

3. Discuss the functions of Database Management Systems (DBMS) in business.

4. Explain the role of Database Management Systems (DBMS) in MIS

5. Mention the importance of database.

6. Do you think that DBMS learning is importance for business professional? Why?

Explain.

7. What are the objectives of Database Management Systems (DBMS) software?

8. Point out the Database Management Systems (DBMS). What are the End users, DBMS,

Database, and DBA? Explain with figure.

9. Define RDBMS. Write importance of RDBMS in MIS.

10. Define database. Write importance of database in business.

11. What are the components of DBMS? Write different type of Databases. Explain

12. What is Data Warehouse? Write benefits of Data Warehouse in MIS. Differentiate between Data

Warehouse and Data mining.

13. Short notes: Records, Database, Key fields, RDBMS, Data warehouse, DBMS, Data mining and

Storage Area network (SAN).

References 1 O Brien, James A.(2004). Management Information Systems, New Delhi: Tata McGraw-Hill Publication Co. Ltd.p.73

2 Hutchinson, et. el (2003), Computer and Information Systems, USA: IRWIN. p.349

3 http://en.wikipedia.org/wiki/Database_system

4 http://en.wikipedia.org/wiki/Computer_software

5 Norton, Peter. (2003). Introduction to Computer, Singapore: McGraw-Hill.p.365

6 http://en.wikipedia.org/wiki/Bibliographic_database

7 http://en.wikipedia.org/wiki/Database

8 http://en.wikipedia.org/wiki/End-user

9 Haag, Stephan et. el. (2006). Business Driven Technology, New York: McGraw-Hil. P. 66

10

Ibid, p.66 11 http://en.wikipedia.org/wiki/Security

12 Laudon and Laudon. (2005). Management Information Systems, New Delhi: Prentice-Hall of India Pvt. Ltd.p224

13 http://encyclopedia2.thefreedictionary.com/Oracle+database

14 Haag, Stephan et. el. (2006). Business Driven Technology, New York: McGraw-Hill. P. 62 15 Haag, Stephan et. el. (2006). Business Driven Technology, New York: McGraw-Hill. P. 74

16 Ibid, p.74-75

17

http://encyclopedia2.thefreedictionary.com/report+writer

Documents

3 Chapter 03 Database DBMS