Assignment Two (2)

UNIVERSITY OF CAPE COAST

COLLEGE OF DISTANCE EDUCATION

DEPARTMENT OF BUSINESS

MASTER OF BUSINESS ADMINISTRATION

BUS 809: MANAGEMENT INFORMATION SYSTEMS

ASSIGNMENT TWO (2)

BY:

SB/DAC/14/0033

CHAPTER SIX (6)

FOUNDATIONS OF BUSINESS INTELLIGENCE: DATABASES AND INFORMATION MANAGEMENT

6.1 ORGANIZING DATA IN A TRADITIONAL FILE ENVIRONMENT

For an organization to have an effective information system that provides users with accurate, timely and relevant information, requires a good and organized data management system. Information is useful when decision makers get it on time and that can be achieved by maintaining an organized data system.

File Organization Terms and Concepts

The computer system organizes data in a hierarchy starting from the least to the highest as follows: Bit and bytes, fields, records, files and databases. Examples are;

Bit: - a character like K, O, F or I.

Field: - combing the characters to form a word like Kofi.

Record: - grouping the fields like Kofi’s Academic details, that, name, course offered, date admitted and grades obtained makes up a record.

Files: - a group of records of same type makes up the file like course details of a number of students.

Databases: - This is made up of a group of related files like a students’ financial file, course file and personal file.

Problems with the Traditional File Environment

The following are some problems with the traditional file environment in most organizations:

Data Redundancy and Inconsistency

Data redundancy is where there is duplicate data in different data files making same data be stored in more than one location. It occurs when different groups in an organization collect data independently and store it independently. In this case an update of file in one group doesn’t automatically update the same record with another group which makes it inconsistent. Example if a student’s name has been updated in the course file it doesn’t update same name at the financial file.

Program-Data Dependence

The traditional file system stores data in specific programs which require that a change in the program will require a change in the data too. For instance, a program used require five letter index number to record a student’s data and if a program which uses a ten letter is installed, the old one becomes less useful as it will not work in the new system and requires a change.

Lack of Flexibility

The traditional file system is too rigid in that, it only produces routine reports but ad hoc reports will be expensive to retrieve with more time.

Poor Security

The traditional system has little control or management of data which makes access to and dissemination of information may be out of control, because there is no way of knowing who is accessing or even making changes to the organization’s data.

Lack of Data Sharing and Availability

Due to the information scattered in different files in different groups in the organization, it is virtually impossible for information to be shared or accessed in a timely manner. Information cannot flow freely across different functional areas or different parts of the organization.

6.2 THE DATABASE APPROACH TO DATA MANAGEMENT

Database is a collection of data organized to serve many applications efficiently by centralizing the data and controlling redundant data. Data is stored in system in one location but shared by all the groups which need it.

Database Management Systems

A database management system (DBMS) is software that permits an organization to centralize data, manage them efficiently, and provide access to the stored data by application programs. The DBMS acts as an intermediary between application programs and the data files. For instance using the DBMS to search for say a name, it will produce all related data concerning the name without requesting then you can choose what you want unlike the traditional system which needs a specific description to find the name for you.

How a DBMS Solves the Problems of the Traditional File Environment

It helps reduces data redundancy

It helps eliminates data inconsistency

It helps get access and availability to information

It helps manage data centrally, its use and security

Relational DBMS

Relational DBMS is a type of database that uses different database models to keep track of entities, attributes, and relationships. Examples of relational DBMS are Microsoft Access, DB2, Oracle Database, and Microsoft SQL. Relational database uses tables which can be combined easily to deliver data required by users, provided that any two tables share a common data element.

Object-Oriented DBMS

Object-oriented DBMS is a database system that can store and retrieve not only structured numbers and characters but also drawings, images, photographs, voice, and full-motion video. Object-oriented DBMS is designed for organizing structured data into rows and columns are not well suited for handling graphics based or multimedia applications.

Capabilities of Database Management Systems

DBMS is capable of organizing, managing and accessing data

DBMS is cable of defining data to specify the structure of the content

It is capable of defining data language, data dictionary and data manipulation language

Designing Databases

To create a database in a company-wide perspective, you must understand the relationships among the data, the type of data that will be maintained in the database, how the data will be used, and how the organization will need to change to manage data.

6.3 USING DATABASES TO IMPROVE BUSINESS PERFORMANCE AND DECISION MAKING

Businesses perform a number of activities such as to keep track of basic transactions, such as paying suppliers, processing orders, keeping track of customers, and paying employees and a use of a database helps to perform such tasks with ease.

Businesses also need databases to provide information that will help the company run its operations more efficiently, and help managers and employees make better decisions. Decisions like knowing which product is the most popular or who is its most profitable customer. These capabilities include data warehousing, data mining, and tools for accessing internal databases through the Web.

Data Warehouse

A data warehouse is a database that stores current and historical data of potential interest to decision makers throughout the company. The data comes in many core operational transaction systems, such as systems for sales, customer accounts, and manufacturing, and from Web site transactions. The data warehouse consolidates and standardizes information from different operational databases so that the information can be used across the enterprise for management analysis and decision making.

The data warehouse makes the data available for anyone to access as needed, but it cannot be altered. A data warehouse system also provides a range of ad hoc and standardized query tools, analytical tools, and graphical reporting facilities

Data Marts

Companies often build enterprise-wide data warehouses, where a central data warehouse serves the entire organization, or they create smaller, decentralized warehouses called data marts. A data mart is a subset or a smaller, decentralized warehouse in which a summarized or highly focused portion of the organization’s data is placed in a separate database for a specific population of users. For example, a company might develop marketing and sales data marts to deal with customer information.

Tools for Business Intelligence: Multidimensional Data Analysis and Data Mining

Business intelligence tools enable users to analyze data to see new patterns, relationships, and insights that are useful for guiding decision making after data has been captured and organized in the data warehouses and data marts. Principal tools for business intelligence include the following:

Online Analytical Processing (OLAP)

OLAP is a system that allows users of data to view same data in a multidimensional manner using different ways using each aspect of information such as product, pricing, cost, region or time period.

OLAP enables users to obtain online answers to ad hoc questions such as, how many washers were sold in the East in June, how that compares with the previous month and the previous June, and how it compares with the sales forecast.

Data Mining

Data mining is more discovery-driven which provides insights into corporate data that cannot be obtained with OLAP by finding hidden patterns and the view that is shows product versus region. The types of information obtainable from data mining include associations, sequences, classifications, clusters, and forecasts.

• Associations are occurrences linked to a single event.

• In sequences, events are linked over time.

• Classification recognizes patterns that describe the group to which an item belongs by examining existing items that have been classified and by inferring a set of rules.

• Clustering works in a manner similar to classification when no groups have yet been defined.

• Although these applications involve predictions, forecasting uses predictions in a different way. It uses a series of existing values to forecast what other values will be.

Text Mining and Web Mining

Text mining tools are used in analyzing unstructured data such as E-mail, memos, call center transcripts, survey responses, legal cases, patent descriptions, and service reports now available to help businesses analyze these data. The Web is another rich source of valuable information, some of which can now be mined for patterns, trends, and insights into customer behavior. Web mining is the discovery and analysis of useful patterns and information from the World Wide Web. For instance, marketers use Google Trends and Google Insights for Search services, which track the popularity of various words and phrases used in Google search queries, to learn what people are interested in and what they are interested in buying.

6.4 MANAGING DATA RESOURCES

After setting up a database, there is the need to make sure that the data for your business remain accurate, reliable, and readily available to decision takers and therefore calls for managing the data resources. The following are some policies for managing data resources:

Establishing an Information Policy

An information policy shows the organization’s rules and regulations for sharing, disseminating, acquiring, standardizing, classifying, and inventorying information. Since the firm’s data is an important resource, there is the need for rules on how to organize and maintain it, who is allowed to view them, rules on procedures and accountability, identifying which users can share, where it can be distributed and who is responsible for updating and maintaining information.

Ensuring Data Quality

The need for setting up an information system that ensures that, data in the organization’s databases are accurate, reliable and consistent. Data that is inaccurate, untimely, or inconsistent with other sources of information lead to incorrect decisions, product recalls, and financial losses. Analysis of data quality often begins with a data quality audit, which is a structured survey of the accuracy and level of completeness of the data in an information system. Data quality audits can be performed by surveying entire data files, surveying samples from data files, or surveying end users for their perceptions of data quality. Data cleansing, also known as data scrubbing, consists of activities for detecting and correcting data in a database that are incorrect, incomplete, improperly formatted, or redundant

Assignment 1

UNIVERSITY OF CAPE COAST

COLLEGE OF DISTANCE EDUCATION

DEPARTMENT OF BUSINESS

MASTER OF BUSINESS ADMINISTRATION

BUS 809: MANAGEMENT INFORMATION SYSTEMS

ASSIGNMENT 1

BY:

SB/DAC/14/0033

SUMMARY OF CHAPTER FOUR (4)

UNDERSTANDING ETHICAL AND SOCIAL ISSUES RELATED TO SYSTEMS

Ethics refers to the principles of right and wrong that individuals, acting as free moral agents, use to make choices to guide their behaviors. Information systems raise new ethical questions for both individuals and societies because they create opportunities for intense social change, and thus threaten existing distributions of power, money, rights, and obligations. Information Technology can be used in the advancement of many social progress as well as commit crimes that will threaten social values.

Some important ethical issues raised by information systems include establishing accountability for the consequences of information systems, setting standards to safeguard system quality that protects the safety of the individual and society, and preserving values and institutions considered essential to the quality of life in an information society.

As a manager or an employee, you will have to decide for yourself what proper legal and ethical conduct your systems should contain. Information systems play a part of most of the instances of failed ethical and legal judgment in most industries. In most cases, the perpetrators of these crimes artfully used financial reporting information systems to cover their decisions from public scrutiny in the vain hope they would never be caught.

Key Technology Trends that raise Ethical Issues

There are four key technological trends responsible for these ethical Issues namely:

The doubling power of computing: The use information systems by most organizations for their core production processes have made it very powerful. As a result of our dependence on systems, the vulnerability to system errors and poor data quality have increased and social rules and laws have not yet adjusted.

Declining Data Storage Cost: Due to advances in data storage techniques and rapidly declining storage costs, organizations have been responsible for the multiplying databases on individuals—employees, customers, and potential customers. These advances in data storage have made the routine violation of individual privacy both cheap and effective.

Advances in data analysis techniques: The resurgence of data analysis techniques for large data has heightened ethical concerns. One is able to find out highly detailed personal information about individuals with ease. With contemporary data management tools, companies can assemble and combine the myriad pieces of information about you stored on computers much more easily than in the past. Some ways to get such information are through credit card purchases, telephone calls, video rentals, banking records, and visits to Web sites among others.

A new data analysis technology called nonobvious relationship awareness (NORA) has given both the government and the private sector even more powerful profiling capabilities. NORA can be used to verify information about people from many disparate sources, such as employment applications, telephone records, customer listings, and “wanted” lists, and correlate relationships to find obscure hidden connections that might help identify criminals or terrorists. The technology is considered a valuable tool for security but its demerit is that, it does have privacy implications in that it can provide such a detailed picture of the activities and associations of a single individual.

Networking advances: The use of mediums such as the Internet have reduced the costs of moving and accessing large quantities of data and open the possibility of mining large pools of data remotely using small desktop machines, permitting an invasion of privacy on a scale and with a precision.

ETHICS IN AN INFORMATION SOCIETY

Ethics is a concern of humans who have freedom of choice. Ethics is about individual choice: When faced with alternative courses of action, what is the correct moral choice? Individuals must be responsible for the consequences of their actions. The main features of ethical choice are as follows:

Responsibility: Responsibility is accepting the potential costs, duties, and obligations for the decisions you make.

Accountability: This means putting in place mechanisms that determines who took responsible action, and who is responsible. Systems and institutions in which it is impossible to find out who took what action are inherently incapable of ethical analysis or ethical action.

Liability: This extends the concept of responsibility further to the area of laws. The body of law in place that, permits individuals to seek redress for the damages done to them by other actors, systems, or organizations. Due process is a related feature of law-governed societies and is a process in which laws are known and understood, and there is an ability to appeal to higher authorities to ensure that the laws are applied correctly.

Ethical Analysis

The following five-step process can be used to analysis ethical issues when confronted with one:

Identify and describe clearly the facts. Find out who did what to whom, and where, when, and how. In many instances, you will be surprised at the errors in the initially reported facts, and often you will find that simply getting the facts straight helps define the solution. It also helps to get the opposing parties involved in an ethical dilemma to agree on the facts.

Define the conflict or dilemma and identify the higher-order values involved. Ethical, social, and political issues always reference higher values. The parties to a dispute all claim to be pursuing higher values (e.g., freedom, privacy, protection of property, and the free enterprise system) especially when an ethical issue involves a dilemma: two diametrically opposed courses of action that support worthwhile values. For example, the needs to improve health care record keeping and the need to protect individual privacy.

Identify the stakeholders. There is the need to identify the players in the game who have an interest in the outcome, who have invested in the situation, and usually who have vocal opinions. Find out the identity of these groups and what they want and this will be useful in designing a solution.

Identify the options that you can reasonably take. You may find that none of the options satisfy all the interests involved, but that some options do a better job than others. Sometimes arriving at a good or ethical solution may not always be a balancing of consequences to stakeholders.

Identify the potential consequences of your options. Some options may be ethically correct but unethical from other points of view. Other options may work in one instance but not in other similar instances. Always ask yourself, “What if I choose this option consistently over time?”

Ethical Principles

The following are ethical principles that help to take decisions and make informed judgments: 

Do unto others as you would have them do unto you (the Golden Rule). This implies that one empathizes and thinking of yourself as the object of the decision can help you think about fairness in decision making.

If an action is not right for everyone to take, it is not right for anyone (Immanuel Kant’s Categorical Imperative). Ask yourself, “If everyone did this, could the organization, or society, survive?”

If an action cannot be taken repeatedly, it is not right to take at all (Descartes’ rule of change). This is the slippery-slope rule: An action may bring about a small change now that is acceptable, but if it is repeated, it would bring unacceptable changes in the long run. Take the action that achieves the higher or greater value by prioritizing values in a rank order and understanding the consequences of various courses of action.

Take the action that produces the least harm or the least potential cost (Risk Aversion Principle). Some actions have extremely high failure costs of very low probability (e.g., building a nuclear generating facility in an urban area) or extremely high failure costs of moderate probability (speeding and automobile accidents). Avoid these high-failure-cost actions, paying greater attention to high-failure-cost potential of moderate to high probability.

Assume that virtually all tangible and intangible objects are owned by someone else unless there is a specific declaration otherwise. (This is the ethical “no free lunch” rule.) If something someone else has created is useful to you, it has value, and you should assume the creator wants compensation for this work. Actions that do not easily pass these rules deserve close attention and a great deal of caution. The appearance of unethical behavior may do as much harm to you and your company as actual unethical behavior.

THE MORAL DIMENSIONS OF INFORMATION SYSTEMS

The major ethical, social, and political issues raised by information systems include the following moral dimensions:

Information rights and obligations: Privacy is the claim of individuals to be left alone, free from surveillance or interference from other individuals or organizations, including the state. Claims to privacy are also involved at the workplace. What information rights do individuals and organizations possess with respect to themselves? What can they protect?

Property rights and obligations: How will traditional intellectual property rights be protected in a digital society in which tracing and accounting for ownership is difficult and ignoring such property rights is so easy? Some examples of property rights are trade secrets, copyrights and patent rights.

Accountability and control: This is concerned about who can and will be held accountable and liable for the harm done to individual and collective information and property rights? Along with privacy and property laws, new information technologies are challenging existing liability laws and social practices for holding individuals and institutions accountable. If a person is injured by a machine controlled, in part, by software, which should be held accountable and, therefore, held liable. What about the Internet? If you outsource your information processing, can you hold the external vendor liable for injuries done to your customers? Some real-world examples may shed light on these questions.

System quality:  What standards of data and system quality should we demand to protect individual rights and the safety of society? The debate over liability and accountability for unintentional consequences of system use raises a related but independent moral dimension: There should be an acceptable, technologically feasible level of system quality where individuals and organizations may be held responsible for avoidable and foreseeable consequences, which they have a duty to perceive and correct. However, some system errors are foreseeable and correctable only at a cost so great that pursuing this level of perfection is not feasible economically—no one could afford the product.

The principal sources of poor system performance are namely software bugs and errors, hardware or facility failures caused by natural or other causes, and poor input data quality

Quality of life: The negative social costs of introducing information technologies and systems are beginning to mount along with the power of the technology. Many of these negative social consequences are not violations of individual rights or property crimes. Nevertheless, these negative consequences can be extremely harmful to individuals, societies, and political institutions. Computers and information technologies potentially can destroy valuable elements of our culture and society even while they bring us benefits. If there is a balance of good and bad consequences of using information systems, who do we hold responsible for the bad consequences? Next, we briefly examine some of the negative social consequences of systems, considering individual, social, and political responses. What values should be preserved in an information- and knowledge-based society? Which institutions should we protect from violation? Which cultural values and practices are supported by the new information technology?