Oper Excell 2. Due in 12 hours

Chapter 3: Software

Learning Objectives

Upon successful completion of this chapter, you will be

able to:

• define the term software;

• identify and describe the two primary categories of

software;

• describe the role ERP software plays in an

organization;

• describe cloud computing and its advantages and

disadvantages for use in an organization; and

• define the term open-source and identify its

primary characteristics.

Introduction

The second component of an information system is software, the

set of instructions that tells the hardware what to do. Software

is created by developers through the process of programming

(covered in more detail in Chapter 10). Without software, the

hardware would not be functional.

54 | Chapter 3: Software

Types of Software

Software can be broadly divided into two categories: operating

systems and application software. Operating systems manage the

hardware and create the interface between the hardware and the

user. Application software performs specific tasks such as word

processing, accounting, database management, video games, or

browsing the web.

Operating Systems

An operating system is first loaded into the computer by the

boot program, then it manages all of the programs in the computer,

including both programs native to the operating system such as

file and memory management and application software. Operating

systems provide you with these key functions:

1. managing the hardware resources of the computer;

2. providing the user-interface components;

Chapter 3: Software | 55

Linux Ubuntu desktop

3. providing a platform for software developers to write

applications.

All computing devices require an operating system. The most

popular operating systems for personal computers are: Microsoft

Windows, Apple’s Mac OS, and various versions of Linux.

Smartphones and tablets run operating systems as well, such as

iOS (Apple), Android (Google), Windows Mobile (Microsoft), and

Blackberry.

Microsoft provided the first operating system for the IBM-PC,

released in 1981. Their initial venture into a Graphical User Interface

(GUI) operating system, known as Windows, occurred in 1985.

Today’s Windows 10 supports the 64-bit Intel CPU. Recall that

“64-bit” indicates the size of data that can be moved within the

computer.

Apple introduced the Macintosh computer 1984 with the first

commercially successful GUI. Apple’s operating system for the

Macintosh is known as “Mac OS ” and also uses an Intel CPU

supporting 64-bit processing. Mac OS versions have been named

after mountains such as El Capitan, Sierra, and High Sierra.

Multitasking, virtual memory, and voice input have become

standard features of both operating systems.

The Linux operating system

is open source, meaning

individual developers are

allowed to make modifications

to the programming code.

Linux is a version of the Unix

operating. Unix runs on large

and expensive minicomputers.

Linux developer Linus Torvalds,

a professor in Finland and the creator of Linux, wanted to find a way

to make Unix run on less expensive personal computers. Linux has

many variations and now powers a large percentage of web servers

in the world.

56 | Information Systems for Business and Beyond (2019)

Sidebar: Why Is Microsoft Software So Dominant in the Business World?

If you’ve worked in business, you may have noticed that almost

all computers in business run a version of Microsoft Windows.

However, in classrooms from elementary to college, there is almost

a balance between Macs and PCs. Why has this not extended into

the business world?

As discussed in Chapter 1, many businesses used IBM mainframe

computers back in the 1960s and 1970s. When businesses migrated

to the microcomputer (personal computer) market, they elected to

stay with IBM and chose the PC. Companies took the safe route,

invested in the Microsoft operating system and in Microsoft

software/applications.

Microsoft soon found itself with the dominant personal computer

operating system for businesses. As the networked PC began to

replace the mainframe computer, Microsoft developed a network

operating system along with a complete suite of programs focused

on business users. Today Microsoft Office in its various forms

controls 85% of the market. 1

Application Software

The second major category of software is application software.

1. [1]

Chapter 3: Software | 57

Image of Microsoft Excel

Application software is utilized directly today to accomplish a

specific goal such as word processing, calculations on a

spreadsheet, or surfing the Internet using your favorite browser.

The “Killer” App

When a new type of digital

device is invented, there are

generally a small group of

technology enthusiasts who

will purchase it just for the joy

of figuring out how it works. A

“killer” application is one that

becomes so essential that large

numbers of people will buy a

device just to run that application. For the personal computer, the

killer application was the spreadsheet.

The first spreadsheet was created by an MBA student at Harvard

University who tired of making repeated calculations to determine

the optimal result on a problem and decided to create a tool that

allowed the user to easily change values and recalculate formulas.

The result was the spreadsheet. Today’s dominant spreadsheet is

Microsoft Excel which still retains the basic functionality of the first

spreadsheet.

Productivity Software

Along with the spreadsheet, several other software applications

have become standard tools for the workplace. Known as

productivity software, these programs allow office employees to

complete their daily work efficiently. Many times these applications

58 | Information Systems for Business and Beyond (2019)

come packaged together, such as in Microsoft’s Office suite. Here is

a list of some of these applications and their basic functions:

• Word processing Users can create and edit documents using this class of software. Functions include the ability to type and

edit text, format fonts and paragraphs, as well as add, move,

and delete text throughout the document. Tables and images

can be inserted. Documents can be saved in a variety of

electronic file formats with Microsoft Word’s DOCX being the

most popular. Documents can also be converted to other

formats such as Adobe’s PDF (Portable Document Format) or a

.TXT file.

• Spreadsheet This class of software provides a way to do numeric calculations and analysis, displaying the result in

charts and graphs. The working area is divided into rows and

columns, where users can enter numbers, text, or formulas. It

is the formulas that make a spreadsheet powerful, allowing the

user to develop complex calculations that can change based on

the numbers entered. The most popular spreadsheet package

is Microsoft Excel, which saves its files in the XLSX format.

• Presentation Users can create slideshow presentations using this class of software. The slides can be projected, printed, or

distributed to interested parties. Text, images, audio, and

visual can all be added to the slides. Microsoft’s PowerPoint is

the most popular software right now, saving its files in PPTX

format.

• Some office suites include other types of software. For

example, Microsoft Office includes Outlook, its e-mail

package, and OneNote, an information-gathering collaboration

tool. The professional version of Office also includes Microsoft

Access, a database package. (Databases are covered more in

Chapter 4.)

Microsoft popularized the idea of the office-software productivity

Chapter 3: Software | 59

bundle with their release of the Microsoft Office Suite. This package

continues to dominate the market and most businesses expect

employees to know how to use this software. However, many

competitors to Microsoft Office do exist and are compatible with

the file formats used by Microsoft (see table below). Microsoft also

offers a cloud-based version of their office suite named Microsoft

Office 365. Similar to Google Drive, this suite allows users to edit

and share documents online utilizing cloud-computing technology.

Utility Software and Programming Software

Utility software includes programs that allow you to fix or modify

your computer in some way. Examples include anti-malware

software and programs that totally remove software you no longer

want installed. These types of software packages were created to

fill shortcomings in operating systems. Many times a subsequent

release of an operating system will include these utility functions as

part of the operating system itself.

Programming software’s purpose is to produce software. Most of

60 | Information Systems for Business and Beyond (2019)

Screen shot of Tableau (click to enlarge)

these programs provide developers with an environment in which

they can write the code, test it, and convert/compile it into the

format that can then be run on a computer. This software is typically

identified as the Integrated Development Environment (IDE) and is

provided free from the corporation that developed the

programming language that will be used to write the code.

Sidebar: “PowerPointed” to Death

As presentation software has

gained acceptance as the

primary method to formally

present information to a group

or class, the art of giving an

engaging presentation is

becoming rare. Many

presenters now just read the

bullet points in the

presentation and immediately bore those in attendance, who can

already read it for themselves. The real problem is not with

PowerPoint as much as it is with the person creating and presenting.

Author and chief evangelist Guy Kawasaki has developed the 10/20/

30 rule for Powerpoint users. Just remember: 10 slides, 20 minutes,

30 point font.” 2 If you are determined to improve your PowerPoint

skills, read Presentation Zen by Garr Reynolds.

New digital presentation technologies are being developed that

go beyond Powerpoint. For example, Prezi uses a single canvas for

the presentation, allowing presenters to place text, images, and

2. [2]

Chapter 3: Software | 61

other media on the canvas, and then navigate between these objects

as they present. Tools such as Tableau allow users to analyze data in

depth and create engaging interactive visualizations.

Sidebar: I Own This Software, Right? Well…

When you purchase software and install it on your computer, are

you the owner of that software? Technically, you are not! When you

install software, you are actually just being given a license to use it.

When you first install a package, you are asked to agree to the terms

of service or the license agreement. In that agreement, you will find

that your rights to use the software are limited. For example, in

the terms of the Microsoft Office software license, you will find

the following statement: “This software is licensed, not sold. This

agreement only gives you some rights to use the features included

in the software edition you licensed.”

For the most part, these restrictions are what you would expect.

You cannot make illegal copies of the software and you may not use

it to do anything illegal. However, there are other, more unexpected

terms in these software agreements. For example, many software

agreements ask you to agree to a limit on liability. Again, from

Microsoft: “Limitation on and exclusion of damages. You can

recover from Microsoft and its suppliers only direct damages up to

the amount you paid for the software. You cannot recover any other

damages, including consequential, lost profits, special, indirect or

incidental damages.” This means if a problem with the software

causes harm to your business, you cannot hold Microsoft or the

supplier responsible for damages.

62 | Information Systems for Business and Beyond (2019)

Applications for the Enterprise

As the personal computer proliferated inside organizations, control

over the information generated by the organization began

splintering. For instance, the customer service department creates

a customer database to keep track of calls and problem reports,

and the sales department also creates a database to keep track of

customer information. Which one should be used as the master

list of customers? Or perhaps someone in sales might create a

spreadsheet to calculate sales revenue, while someone in finance

creates a different revenue document that meets the needs of their

department, but calculates revenue differently. The two

spreadsheets will report different revenue totals. Which one is

correct? And who is managing all of this information?

Enterprise Resource Planning

In the 1990s

the need to bring an organization’s information back under

centralized control became more apparent. The Enterprise

Resource Planning (ERP) system (sometimes just called enterprise

software) was developed to bring together an entire organization

within one program. ERP software utilizes a central database that

is implemented throughout the entire organization. Here are some

key points about ERP.

• A software application. ERP is an application that is used by

Chapter 3: Software | 63

many of an organization’s employees.

• Utilizes a central database. All users of the ERP edit and save their information from the same data source. For example, this

means there is only one customer table in the database, there

is only one sales (revenue) table in the database, etc.

• Implemented organization-wide. ERP systems include functionality that covers all of the essential components of a

business. An organization can purchase modules for its ERP

system that match specific needs such as order entry,

manufacturing, or planning.

ERP systems were originally marketed to large corporations.

However, as more and more large companies began installing them,

ERP vendors began targeting mid-sized and even smaller

businesses. Some of the more well-known ERP systems include

those from SAP, Oracle, and Microsoft.

In order to effectively implement an ERP system in an

organization, the organization must be ready to make a full

commitment. All aspects of the organization are affected as old

systems are replaced by the ERP system. In general, implementing

an ERP system can take two to three years and cost several million

dollars.

So why implement an ERP system? If done properly, an ERP

system can bring an organization a good return on their investment.

By consolidating information systems across the enterprise and

using the software to enforce best practices, most organizations

see an overall improvement after implementing an ERP. Business

processes as a form of competitive advantage will be covered in

Chapter 9.

64 | Information Systems for Business and Beyond (2019)

Customer Relationship Management

A Customer Relationship Management (CRM) system manages an

organization’s customers. In today’s environment, it is important to

develop relationships with your customers, and the use of a well-

designed CRM can allow a business to personalize its relationship

with each of its customers. Some ERP software systems include

CRM modules. An example of a well-known CRM package is

Salesforce.

Supply Chain Management

Supply Chain

Many organizations must deal with the complex task of managing

their supply chains. At its simplest, a supply chain is the linkage

between an organization’s suppliers, its manufacturing facilities,

and the distributors of its products. Each link in the chain has a

multiplying effect on the complexity of the process. For example,

if there are two suppliers, one manufacturing facility, and two

distributors, then the number of links to manage = 4 ( 2 x 1 x

2 ). However, if two more suppliers are added, plus another

manufacturing facility, and two more distributors, then the number

of links to manage = 32 ( 4 x 2 x 4 ). Also, notice in the above

illustration that all arrows have two heads, indicating that

information flows in both directions. Suppliers are part of a

business’s supply chain. They provide information such as price,

size, quantity, etc. to the business. In turn, the business provides

information such as quantity on hand at every store to the supplier.

The key to successful supply chain management is the information

system.

Chapter 3: Software | 65

A Supply Chain Management (SCM) system handles the

interconnection between these links as well as the inventory of

the products in their various stages of development. As discussed

previously much of Walmart’s success has come from its ability

to identify and control the supply chain for its products. Walmart

invested heavily in their information system so they could

communicate with their suppliers and manage the thousands of

products they sell.

Walmart realized in the 1980s that the key to their success was

information systems. Specifically, they needed to manage their

complex supply chain with its thousands of suppliers, thousands

of retail outlets, and millions of customers. Their success came

from being able to integrate information systems to every entity

(suppliers, warehouses, retail stores) through the sharing of sales

and inventory data. Take a moment to study the diagram

above…look for the double-headed arrow. Notice that data flows

down the supply chain from suppliers to retail stores. But it also

flows up the supply chain, back to the suppliers so they can be up to

date regarding production and shipping.

Mobile Applications

Just as with the personal computer, mobile devices such as

66 | Information Systems for Business and Beyond (2019)

smartphones and electronic tablets also have operating systems and

application software. These mobile devices are in many ways just

smaller versions of personal computers. A mobile app is a software

application designed to run specifically on a mobile device.

As shown in Chapter 2, smartphones are becoming a dominant

form of computing, with more smartphones being sold than

personal computers. A greater discussion of PC and smartphone

sales appears in Chapter 13, along with statistics regarding the

decline in tablet sales. Businesses have adjusted to this trend by

increasing their investment in the development of apps for mobile

devices. The number of mobile apps in the Apple App Store has

increased from zero in 2008 to over 2 million in 2017. 3

Building a mobile app will will be covered in Chapter 10.

Cloud Computing

Historically, for software to run on a computer an individual copy

of the software had to be installed on the computer. The concept of

“cloud” computing changes this.

Cloud Computing

The “cloud” refers to applications, services, and data storage

located on the Internet. Cloud service providers rely on giant server

farms and massive storage devices that are connected via the

Internet. Cloud computing allows users to access software and data

storage services on the Internet.

You probably already use cloud computing in some form. For

example, if you access your e-mail via your web browser, you are

3. [3]

Chapter 3: Software | 67

using a form of cloud computing if you are using Google Drive’s

applications. While these are free versions of cloud computing,

there is big business in providing applications and data storage over

the web. Cloud computing is not limited to web applications. It can

also be used for services such as audio or video streaming.

Advantages of Cloud Computing

• No software to install or upgrades to maintain.

• Available from any computer that has access to the Internet.

• Can scale to a large number of users easily.

• New applications can be up and running very quickly.

• Services can be leased for a limited time on an as-needed

basis.

• Your information is not lost if your hard disk crashes or your

laptop is lost or stolen.

• You are not limited by the available memory or disk space on

your computer.

Disadvantages of Cloud Computing

• Your information is stored on someone else’s computer.

• You must have Internet access to use it.

• You are relying on a third-party to provide these services.

Cloud computing has the ability to really impact how

organizations manage technology. For example, why is an IT

department needed to purchase, configure, and manage personal

computers and software when all that is really needed is an Internet

connection?

68 | Information Systems for Business and Beyond (2019)

Using a Private Cloud

Many organizations are understandably nervous about giving up

control of their data and some of their applications by using cloud

computing. But they also see the value in reducing the need for

installing software and adding disk storage to local computers. A

solution to this problem lies in the concept of a private cloud. While

there are various models of a private cloud, the basic idea is for

the cloud service provider to section off web server space for a

specific organization. The organization has full control over that

server space while still gaining some of the benefits of cloud

computing.

Virtualization

Virtualization is the process of using software to simulate a

computer or some other device. For example, using virtualization

a single physical computer can perform the functions of several

virtual computers, usually referred to as Virtual Machines (VMs).

Organizations implement virtual machines in an effort to reduce

the number of physical servers needed to provide the necessary

services to users. This reduction in the number of physical servers

also reduces the demand for electricity to run and cool the physical

servers. For more detail on how virtualization works, see this

informational page from VMWare.

Chapter 3: Software | 69

Example program “Hello World” written in Java

Software Creation

Modern software applications

are written using a

programming language such as

Java, Visual C, C++, Python, etc.

A programming language

consists of a set of commands

and syntax that can be

organized logically to execute

specific functions. Using this language a programmer writes a

program (known as source code) that can then be compiled into

machine-readable form, the ones and zeroes necessary to be

executed by the CPU. Languages such as HTML and Javascript are

used to develop web pages.

Open-Source Software

When the personal computer was first released, computer

enthusiasts banded together to build applications and solve

problems. These computer enthusiasts were motivated to share any

programs they built and solutions to problems they found. This

collaboration enabled them to more quickly innovate and fix

problems.

As software began to become a business, however, this idea of

sharing everything fell out of favor with many developers. When a

program takes hundreds of hours to develop, it is understandable

that the programmers do not want to just give it away. This led to a

new business model of restrictive software licensing which required

payment for software, a model that is still dominant today. This

model is sometimes referred to as closed source, as the source code

is not made available to others.

70 | Information Systems for Business and Beyond (2019)

There are many, however, who feel that software should not be

restricted. Just as with those early hobbyists in the 1970s, they feel

that innovation and progress can be made much more rapidly if

they share what has been learned. In the 1990s, with Internet access

connecting more people together, the open-source movement

gained steam.

Open Office Suite

Open-source software makes the source code available for

anyone to copy and use. For most people having access to the

source code of a program does little good since it is challenging to

modify existing programming code. However, open-source software

is also available in a compiled format that can be downloaded and

installed. The open-source movement has led to the development

of some of the most used software in the world such as the Firefox

browser, the Linux operating system, and the Apache web server.

Many businesses are wary of open-source software precisely

because the code is available for anyone to see. They feel that this

increases the risk of an attack. Others counter that this openness

actually decreases the risk because the code is exposed to

thousands of programmers who can incorporate code changes to

quickly patch vulnerabilities.

There are thousands of open-source applications available for

download. For example, you can get the productivity suite from

Chapter 3: Software | 71

Open Office. One good place to search for open-source software is

sourceforge.net, where thousands of programs are available for free

download.

Summary

Software gives the instructions that tell the hardware what to do.

There are two basic categories of software: operating systems and

applications. Operating systems interface with the computer

hardware and make system resources available. Application

software allows users to accomplish specific tasks such as word

processing, presentations, or databases. This group is also referred

to as productivity software. An ERP system stores all data in a

centralized database that is made accessible to all programs and

departments across the organization. Cloud computing provides

access to software and databases from the Internet via a web

browser. Developers use various programming languages to develop

software.

Study Questions

1. Develop your own definition of software being certain to

explain the key terms.

2. What are the primary functions of an operating system?

3. Which of the following are operating systems and which are

applications: Microsoft Excel, Google Chrome, iTunes,

Windows, Android, Angry Birds.

4. What is your favorite software application? What tasks does it

help you accomplish?

72 | Information Systems for Business and Beyond (2019)

5. How would you categorize the software that runs on mobile

devices? Break down these apps into at least three basic

categories and give an example of each.

6. What does an ERP system do?

7. What is open-source software? How does it differ from closed-

source software? Give an example of each.

8. What does a software license grant to the purchaser of the

software?

Exercises

1. Find a case study online about the implementation of an ERP

system. Was it successful? How long did it take? Does the case

study tell you how much money the organization spent?

2. If you were running a small business with limited funds for

information technology, would you consider using cloud

computing? Find some web-based resources that support your

decision.

3. Go to sourceforge.net and review their most downloaded

software applications. Report on the variety of applications you

find. Then pick one that interests you and report back on what

it does, the kind of technical support offered, and the user

reviews.

4. Review this article on the security risks of open-source

software. Write a short analysis giving your opinion on the

different risks discussed.

5. List three examples of programming languages? What features

in each language makes it useful to developers?

Chapter 3: Software | 73

Lab

1. Download Apache Open Office and create a document. Note: If

your computer does not have Java Runtime Environment (JRE)

32-bit (x86) installed, you will need to download it first from

this site.Open Office runs only in 32-bit (x86) mode. Here is a

link to the Getting Started documentation for Open Office.

How does it compare to Microsoft Office? Does the fact that

you got it for free make it feel less valuable?

1. Statista. (2017). Microsoft – Statistics & Facts. Retrieved from

https://www.statista.com/topics/823/microsoft/

2. Kawasaki, G. (n.d.). The 10/20/30 Rules for PowerPoint.

Retrieved from https://guykawasaki.com/the_102030_rule/.↵

3. Statista. (2018). Number of apps in Apple App Store July 2008 to

January 2017. Retrieved from https:https://www.statista.com/

statistics/263795/number-of-available-apps-in-the-apple-

app-store/.↵

74 | Information Systems for Business and Beyond (2019)

Chapter 4: Data and Databases

Learning Objectives

Upon successful completion of this chapter, you

will be able to:

• Describe the differences between data,

information, and knowledge;

• Describe why database technology must be

used for data resource management;

• Define the term database and identify the

steps to creating one;

• Describe the role of a database

management system;

• Describe the characteristics of a data

warehouse; and

• Define data mining and describe its role in

an organization.

Chapter 4: Data and Databases | 75

Introduction

You have already been introduced to the first two components of

information systems: hardware and software. However, those two

components by themselves do not make a computer useful. Imagine

if you turned on a computer, started the word processor, but could

not save a document. Imagine if you opened a music player but

there was no music to play. Imagine opening a web browser but

there were no web pages. Without data, hardware and software

are not very useful! Data is the third component of an information

system.

Data, Information, and Knowledge

There have been many definitions and theories about data,

information, and knowledge. The three terms are often used

interchangeably, although they are distinct in nature. We define

and illustrate the three terms from the perspective of information

systems.

76 | Information Systems for Business and Beyond (2019)

Data are the raw facts, and may

be devoid of context or intent. For example, a sales order of

computers is a piece of data. Data can be quantitative or qualitative.

Quantitative data is numeric, the result of a measurement, count,

or some other mathematical calculation. Qualitative data is

descriptive. “Ruby Red,” the color of a 2013 Ford Focus, is an example

of qualitative data. A number can be qualitative too: if I tell you my

favorite number is 5, that is qualitative data because it is descriptive,

not the result of a measurement or mathematical calculation.

Information is processed data that possess context, relevance, and

purpose. For example, monthly sales calculated from the collected

daily sales data for the past year are information. Information

typically involves the manipulation of raw data to obtain an

indication of magnitude, trends, in patterns in the data for a

purpose.

Knowledge in a certain area is human beliefs or perceptions about

relationships among facts or concepts relevant to that area. For

example, the conceived relationship between the quality of goods

Chapter 4: Data and Databases | 77

and the sales is knowledge. Knowledge can be viewed as

information that facilitates action.

Once we have put our data into context, aggregated and analyzed

it, we can use it to make decisions for our organization. We can

say that this consumption of information produces knowledge. This

knowledge can be used to make decisions, set policies, and even

spark innovation.

Explicit knowledge typically refers to knowledge that can be

expressed into words or numbers. In contrast, tacit knowledge

includes insights and intuitions, and is difficult to transfer to

another person by means of simple communications.

Evidently, when information or explicit knowledge is captured

and stored in computer, it would become data if the context or

intent is devoid.

The final step up the information ladder is the step from

knowledge (knowing a lot about a topic) to wisdom. We can say

that someone has wisdom when they can combine their knowledge

and experience to produce a deeper understanding of a topic. It

often takes many years to develop wisdom on a particular topic, and

requires patience.

Big Data

Almost all software programs require data to do anything useful.

For example, if you are editing a document in a word processor

such as Microsoft Word, the document you are working on is the

data. The word-processing software can manipulate the data: create

a new document, duplicate a document, or modify a document.

Some other examples of data are: an MP3 music file, a video file, a

spreadsheet, a web page, a social media post, and an e-book.

Recently, big data has been capturing the attention of all types of

organizations. The term refers to such massively large data sets that

conventional data processing technologies do not have sufficient

78 | Information Systems for Business and Beyond (2019)

power to analyze them. For example, Walmart must process millions

customer transactions every hour across the world. Storing and

analyzing that much data is beyond the power of traditional data

management tools. Understanding and developing the best tools

and techniques to manage and analyze these large data sets are a

problem that governments and businesses alike are trying to solve.

Databases

The goal of many information systems is to transform data into

information in order to generate knowledge that can be used for

decision making. In order to do this, the system must be able to take

data, allow the user to put the data into context, and provide tools

for aggregation and analysis. A database is designed for just such a

purpose.

Why Databases?

Data is a valuable resource in the organization. However, many

people do not know much about database technology, but use non-

database tools, such as Excel spreadsheet or Word document, to

store and manipulate business data, or use poorly designed

databases for business processes. As a result, the data are

redundant, inconsistent, inaccurate, and corrupted. For a small

data set, the use of non-database tools such as spreadsheet may

not cause serious problem. However, for a large organization,

corrupted data could lead to serious errors and destructive

consequences. The common defects in data resources management

are explained as follows.

(1) No control of redundant data

People often keep redundant data for convenience. Redundant

Chapter 4: Data and Databases | 79

data could make the data set inconsistent. We use an illustrative

example to explain why redundant data are harmful. Suppose the

registrar’s office has two separate files that store student data: one

is the registered student roster which records all students who have

registered and paid the tuition, and the other is student grade roster

which records all students who have received grades.

As you can see from the two spreadsheets, this data management

system has problems. The fact that “Student 4567 is Mary Brown,

and her major is Finance” is stored more than once. Such

occurrences are called data redundancy. Redundant data often

make data access convenient, but can be harmful. For example, if

Mary Brown changes her name or her major, then all her names and

major stored in the system must be changed altogether. For small

data systems, such a problem looks trivial. However, when the data

system is huge, making changes to all redundant data is difficult if

not impossible. As a result of data redundancy, the entire data set

can be corrupted.

(2) Violation of data integrity

Data integrity means consistency among the stored data. We

use the above illustrative example to explain the concept of data

integrity and how data integrity can be violated if the data system is

flawed. You can find that Alex Wilson received a grade in MKT211;

however, you can’t find Alex Wilson in the student roster. That is,

the two rosters are not consistent. Suppose we have a data integrity

control to enforce the rules, say, “no student can receive a grade

unless she/he has registered and paid tuition”, then such a violation

of data integrity can never happen.

(3) Relying on human memory to store and to search needed data

The third common mistake in data resource management is the

80 | Information Systems for Business and Beyond (2019)

over use of human memory for data search. A human can remember

what data are stored and where the data are stored, but can also

make mistakes. If a piece of data is stored in an un-remembered

place, it has actually been lost. As a result of relying on human

memory to store and to search needed data, the entire data set

eventually becomes disorganized.

To avoid the above common flaws in data resource management,

database technology must be applied. A database is an organized

collection of related data. It is an organized collection, because in

a database, all data is described and associated with other data.

For the purposes of this text, we will only consider computerized

databases.

Though not good for replacing databases, spreadsheets can be

ideal tools for analyzing the data stored in a database. A spreadsheet

package can be connected to a specific table or query in a database

and used to create charts or perform analysis on that data.

Data Models and Relational Databases

Databases can be organized in many different ways by using

different models. The data model of a database is the logical

structure of data items and their relationships. There have been

several data models. Since the 1980s, the relational data model

has been popularized. Currently, relational database systems are

commonly used in business organizations with few exceptions. A

relational data model is easy to understand and use.

In a relational database, data is organized into tables (or relations).

Each table has a set of fields which define the structure of the data

stored in the table. A record is one instance of a set of fields in a

table. To visualize this, think of the records as the rows (or tuple) of

the table and the fields as the columns of the table.

In the example below, we have a table of student data, with each

row representing a student record , and each column representing

Chapter 4: Data and Databases | 81

one filed of the student record. A special filed or a combination

of fields that determines the unique record is called primary key

(or key). A key is usually the unique identification number of the

records.

Rows and columns in a table

Designing a Database

Suppose a university wants to create a School Database to track

data. After interviewing several people, the design team learns that

the goal of implementing the system is to give better insight into

students’ performance and academic resources. From this, the

team decides that the system must keep track of the students, their

grades, courses, and classrooms. Using this information, the design

team determines that the following tables need to be created:

• STUDENT: student name, major, and e-mail.

• COURSE: course title, enrollment capacity.

• GRADE: this table will correlate STUDENT with COURSE,

allowing us to have any given student to enroll multiple

courses and to receive a grade for each course.

• CLASSROOM: classroom location, classroom type, and

classroom capacity

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Now that the design team has determined which tables to create,

they need to define the specific data items that each table will hold.

This requires identifying the fields that will be in each table. For

example, course title would be one of the fields in the COURSE

table. Finally, since this will be a relational database, every table

should have a field in common with at least one other table (in other

words, they should have relationships with each other).

A primary key must be selected for each table in a relational

database. This key is a unique identifier for each record in the table.

For example, in the STUDENT table, it might be possible to use the

student name as a way to identify a student. However, it is more

than likely that some students share the same name. A student’s

e-mail address might be a good choice for a primary key, since e-

mail addresses are unique. However, a primary key cannot change,

so this would mean that if students changed their e-mail address we

would have to remove them from the database and then re-insert

them – not an attractive proposition. Our solution is to use student

ID as the primary key of the STUDENT table. We will also do this

for the COURSE table and the CLASSROOM table. This solution is

quite common and is the reason you have so many IDs! The primary

key of table can be just one field, but can also be a combination of

two or more fields. For example, the combination of StudentID and

CourseID the GRADE table can be the primary key of the GRADE

table, which means that a grade is received by a particular student

for a specific course.

The next step of design of database is to identify and make the

relationships between the tables so that you can pull the data

together in meaningful ways. A relationship between two tables is

implemented by using a foreign key. A foreign key is a field in one

table that connects to the primary key data in the original table. For

example, ClassroomID in the COURSE table is the foreign key that

connects to the primary key ClassroomID in the CLASSROOM table.

With this design, not only do we have a way to organize all of the

data we need and have successfully related all the table together to

Chapter 4: Data and Databases | 83

Tables of the student database

meet the requirements, but have also prevented invalid data from

being entered into the database. You can see the final database

design in the figure below:

Normalization

When designing a database, one important concept to understand

is normalization. In simple terms, to normalize a database means to

design it in a way that: 1) reduces data redundancy; and 2) ensure

data integrity.

In the School Database design, the design team worked to achieve

these objectives. For example, to track grades, a simple (and wrong)

solution might have been to create a Student field in the COURSE

table and then just list the names of all of the students there.

However, this design would mean that if a student takes two or

more courses, then his or her data would have to be entered twice

or more times. This means the data are redundant. Instead, the

designers solved this problem by introducing the GRADE table.

In this design, when a student registers into the school system

before taking a course, we first must add the student to the

STUDENT table, where their ID, name, major, and e-mail address

are entered. Now we will add a new entry to denote that the

student takes a specific course. This is accomplished by adding a

record with the StudentD and the CourseID in the GRADE table.

If this student takes a second course, we do not have to duplicate

the entry of the student’s name, major, and e-mail; instead, we

84 | Information Systems for Business and Beyond (2019)

only need to make another entry in the GRADE table of the second

course’s ID and the student’s ID.

The design of the School database also makes it simple to change

the design without major modifications to the existing structure.

For example, if the design team were asked to add functionality

to the system to track instructors who teach the courses, we could

easily accomplish this by adding a PROFESSOR table (similar to the

STUDENT table) and then adding a new field to the COURSE table

to hold the professors’ ID.

Data Types

When defining the fields in a database table, we must give each field

a data type. For example, the field StudentName is text string, while

EnrollmentCapacity is number. Most modern databases allow for

several different data types to be stored. Some of the more common

data types are listed here:

• Text: for storing non-numeric data that is brief, generally

under 256 characters. The database designer can identify the

maximum length of the text.

• Number: for storing numbers. There are usually a few different

number types that can be selected, depending on how large

the largest number will be.

• Boolean: a data type with only two possible values, such as 0 or

1, “true” or “false”, “yes” or “no”.

• Date/Time: a special form of the number data type that can be

interpreted as a number or a time.

• Currency: a special form of the number data type that formats

all values with a currency indicator and two decimal places.

• Paragraph Text: this data type allows for text longer than 256

characters.

• Object: this data type allows for the storage of data that cannot

Chapter 4: Data and Databases | 85

Open Office Database Management System

be entered via keyboard, such as an image or a music file.

There are two important reasons that we must properly define

the data type of a field. First, a data type tells the database what

functions can be performed with the data. For example, if we wish

to perform mathematical functions with one of the fields, we must

be sure to tell the database that the field is a number data type. For

example, we can subtract the course capacity from the classroom

capacity to find out the number of extra seats available.

The second important reason to define data type is so that the

proper amount of storage space is allocated for our data. For

example, if the StudentName field is defined as a Text(50) data type,

this means 50 characters are allocated for each name we want to

store. If a student’s name is longer than 50 characters, the database

will truncate it.

Database Management Systems

To the computer, a database

looks like one or more files. In

order for the data in the

database to be stored, read,

changed, added, or removed, a

software program must access

it. Many software applications

have this ability: iTunes can

read its database to give you a listing of its songs (and play the

songs); your mobile-phone software can interact with your list of

contacts. But what about applications to create or manage a

database? What software can you use to create a database, change

a database’s structure, or simply do analysis? That is the purpose of

a category of software applications called database management

systems (DBMS).

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DBMS packages generally provide an interface to view and change

the design of the database, create queries, and develop reports.

Most of these packages are designed to work with a specific type

of database, but generally are compatible with a wide range of

databases.

A database that can only be used by a single user at a time is not

going to meet the needs of most organizations. As computers have

become networked and are now joined worldwide via the Internet,

a class of database has emerged that can be accessed by two, ten,

or even a million people. These databases are sometimes installed

on a single computer to be accessed by a group of people at a

single location. Other times, they are installed over several servers

worldwide, meant to be accessed by millions. In enterprises the

relational DBMS are built and supported by companies such as

Oracle, Microsoft SQL Server, and IBM Db2. The open-source

MySQL is also an enterprise database.

Microsoft Access and Open Office Base are examples of personal

database-management systems. These systems are primarily used

to develop and analyze single-user databases. These databases are

not meant to be shared across a network or the Internet, but are

instead installed on a particular device and work with a single user

at a time. Apache OpenOffice.org Base (see screen shot) can be

used to create, modify, and analyze databases in open-database

(ODB) format. Microsoft’s Access DBMS is used to work with

databases in its own Microsoft Access Database format. Both Access

and Base have the ability to read and write to other database

formats as well.

Structured Query Language

Once you have a database designed and loaded with data, how

will you do something useful with it? The primary way to work

Chapter 4: Data and Databases | 87

with a relational database is to use Structured Query Language,

SQL (pronounced “sequel,” or simply stated as S-Q-L). Almost all

applications that work with databases (such as database

management systems, discussed below) make use of SQL as a way to

analyze and manipulate relational data. As its name implies, SQL is a

language that can be used to work with a relational database. From

a

simple request for data to a complex update operation, SQL is a

mainstay of programmers and database administrators. To give you

a taste of what SQL might look like, here are a couple of examples

using our School database:

The following query will retrieve the major of student John

Smith from the STUDENT table:

SELECT StudentMajor FROM STUDENT WHERE StudentName = ‘John Smith’;

The following query will list the total number of students in

the STUDENT table:

SELECT COUNT(*) FROM STUDENT;

SQL can be embedded in many computer languages that are used

to develop platform-independent web-based applications. An in-

depth description of how SQL works is beyond the scope of this

introductory text, but these examples should give you an idea of

the power of using SQL to manipulate relational databases. Many

DBMS, such as Microsoft Access, allow you to use QBE (Query-by-

Example), a graphical query tool, to retrieve data though visualized

commands. QBE generates SQL for you, and is easy to use. In

comparison with SQL, QBE has limited functionalities and is unable

to work without the DBMS environment.

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Other Types of Databases

The relational database model is the most used database model

today. However, many other database models exist that provide

different strengths than the relational model. The hierarchical

database model, popular in the 1960s and 1970s, connected data

together in a hierarchy, allowing for a parent/child relationship

between data. The document-centric model allowed for a more

unstructured data storage by placing data into “documents” that

could then be manipulated.

Perhaps the most interesting new development is the concept

of NoSQL (from the phrase “not only SQL”). NoSQL arose from the

need to solve the problem of large-scale databases spread over

several servers or even across the world. For a relational database

to work properly, it is important that only one person be able to

manipulate a piece of data at a time, a concept known as record-

locking. But with today’s large-scale databases (think Google and

Amazon), this is just not possible. A NoSQL database can work with

data in a looser way, allowing for a more unstructured environment,

communicating changes to the data over time to all the servers that

are part of the database.

As stated earlier, the relational database model does not scale

well. The term scale here refers to a database getting larger

and larger, being distributed on a larger number of computers

connected via a network. Some companies are looking to provide

large-scale database solutions by moving away from the relational

model to other, more flexible models. For example, Google now

offers the App Engine Datastore, which is based on NoSQL.

Developers can use the App Engine Datastore to develop

applications that access data from anywhere in the world.

Amazon.com offers several database services for enterprise use,

including Amazon RDS, which is a relational database service, and

Amazon DynamoDB, a NoSQL enterprise solution.

Chapter 4: Data and Databases | 89

Sidebar: What Is Metadata?

The term metadata can be understood as “data about data.”

Examples of metadata of database are:

• number of records

• data type of field

• size of field

• description of field

• default value of field

• rules of use.

When a database is being designed, a “data dictionary” is created to

hold the metadata, defining the fields and structure of the database.

Finding Value in Data: Business Intelligence

With the rise of Big Data and a myriad of new tools and techniques

at their disposal, businesses are learning how to use information to

their advantage. The term business intelligence is used to describe

the process that organizations use to take data they are collecting

and analyze it in the hopes of obtaining a competitive advantage.

Besides using their own data, stored in data warehouses (see below),

firms often purchase information from data brokers to get a big-

picture understanding of their industries and the economy. The

results of these analyses can drive organizational strategies and

provide competitive advantage.

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Data Visualization

Data visualization is the graphical representation of information and

data. These graphical representations (such as charts, graphs, and

maps) can quickly summarize data in a way that is more intuitive

and can lead to new insights and understandings. Just as a picture

of a landscape can convey much more than a paragraph of text

attempting to describe it, graphical representation of data can

quickly make meaning of large amounts of data. Many times,

visualizing data is the first step towards a deeper analysis and

understanding of the data collected by an organization. Examples of

data visualization software include Tableau and Google Data Studio.

Data Warehouses

As organizations have begun to utilize databases as the centerpiece

of their operations, the need to fully understand and leverage the

data they are collecting has become more and more apparent.

However, directly analyzing the data that is needed for day-to-day

operations is not a good idea; we do not want to tax the operations

of the company more than we need to. Further, organizations also

want to analyze data in a historical sense: How does the data we

have today compare with the same set of data this time last month,

or last year? From these needs arose the concept of the data

warehouse.

The concept of the data warehouse is simple: extract data from

one or more of the organization’s databases and load it into the

data warehouse (which is itself another database) for storage and

analysis. However, the execution of this concept is not that simple.

A data warehouse should be designed so that it meets the following

criteria:

• It uses non-operational data. This means that the data

Chapter 4: Data and Databases | 91

Data Warehouse Process (top-down)

warehouse is using a copy of data from the active databases

that the company uses in its day-to-day operations, so the

data warehouse must pull data from the existing databases on

a regular, scheduled basis.

• The data is time-variant. This means that whenever data is

loaded into the data warehouse, it receives a time stamp,

which allows for comparisons between different time periods.

• The data is standardized. Because the data in a data warehouse

usually comes from several different sources, it is possible that

the data does not use the same definitions or units. For

example, each database uses its own format for dates (e.g.,

mm/dd/yy, or dd/mm/yy, or yy/mm/dd, etc.). In order for

the data warehouse to match up dates, a standard date format

would have to be agreed upon and all data loaded into the data

warehouse would have to be converted to use this standard

format. This process is called extraction-transformation-load

(ETL).

There are two primary schools of thought when designing a data

warehouse: bottom-up and top-down. The bottom-up approach

starts by creating small data warehouses, called data marts, to solve

specific business problems. As these data marts are created, they

can be combined into a larger data warehouse. The top- down

approach suggests that we should start by creating an enterprise-

wide data warehouse and then, as specific business needs are

identified, create smaller data marts from the data warehouse.

Benefits of Data Warehouses

Organizations find data

warehouses quite beneficial for a number of reasons:

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• The process of developing a data warehouse forces an

organization to better understand the data that it is currently

collecting and, equally important, what data is not being

collected.

• A data warehouse provides a centralized view of all data being

collected across the enterprise and provides a means for

determining data that is inconsistent.

• Once all data is identified as consistent, an organization can

generate “one version of the truth”. This is important when the

company wants to report consistent statistics about itself,

such as revenue or number of employees.

• By having a data warehouse, snapshots of data can be taken

over time. This creates a historical record of data, which allows

for an analysis of trends.

• A data warehouse provides tools to combine data, which can

provide new information and analysis.

Data Mining and Machine Learning

Data mining is the process of analyzing data to find previously

unknown and interesting trends, patterns, and associations in order

to make decisions. Generally, data mining is accomplished through

automated means against extremely large data sets, such as a data

warehouse. Some examples of data mining include:

• An analysis of sales from a large grocery chain might

determine that milk is purchased more frequently the day after

it rains in cities with a population of less than 50,000.

• A bank may find that loan applicants whose bank accounts

show particular deposit and withdrawal patterns are not good

credit risks.

• A baseball team may find that collegiate baseball players with

specific statistics in hitting, pitching, and fielding make for

Chapter 4: Data and Databases | 93

more successful major league players.

One data mining method that an organization can use to do these

analyses is called machine learning. Machine learning is used to

analyze data and build models without being explicitly programmed

to do so. Two primary branches of machine learning exist:

supervised learning and unsupervised learning.

Supervised learning occurs when an organization has data about

past activity that has occurred and wants to replicate it. For

example, if they want to create a new marketing campaign for a

particular product line, they may look at data from past marketing

campaigns to see which of their consumers responded most

favorably. Once the analysis is done, a machine learning model is

created that can be used to identify these new customers. It is called

“supervised” learning because we are directing (supervising) the

analysis towards a result (in our example: consumers who respond

favorably). Supervised learning techniques include analyses such as

decision trees, neural networks, classifiers, and logistic regression.

Unsupervised learning occurs when an organization has data and

wants to understand the relationship(s) between different data

points. For example, if a retailer wants to understand purchasing

patterns of its customers, an unsupervised learning model can be

developed to find out which products are most often purchased

together or how to group their customers by purchase history. Is

it called “unsupervised” learning because no specific outcome is

expected. Unsupervised learning techniques include clustering and

association rules.

Privacy Concerns

The increasing power of data mining has caused concerns for many,

especially in the area of privacy. In today’s digital world, it is

becoming easier than ever to take data from disparate sources and

94 | Information Systems for Business and Beyond (2019)

combine them to do new forms of analysis. In fact, a whole industry

has sprung up around this technology: data brokers. These firms

combine publicly accessible data with information obtained from

the government and other sources to create vast warehouses of

data about people and companies that they can then sell. This

subject will be covered in much more detail in chapter 12 – the

chapter on the ethical concerns of information systems.

Sidebar: What is data science? What is data analytics?

The term “data science” is a popular term meant to describe the

analysis of large data sets to find new knowledge. For the past

several years, it has been considered one of the best career fields

to get into due to its explosive growth and high salaries. While a

data scientist does many different things, their focus is generally

on analyzing large data sets using various programming methods

and software tools to create new knowledge for their organization.

Data scientists are skilled in machine learning and data visualization

techniques. The field of data science is constantly changing, and

data scientists are on the cutting edge of work in areas such as

artificial intelligence and neural networks.

Knowledge Management

We end the chapter with a discussion on the concept of knowledge

management (KM). All companies accumulate knowledge over the

Chapter 4: Data and Databases | 95

course of their existence. Some of this knowledge is written down

or saved, but not in an organized fashion. Much of this knowledge

is not written down; instead, it is stored inside the heads of its

employees. Knowledge management is the process of creating,

formalizing the capture, indexing, storing, and sharing of the

company’s knowledge in order to benefit from the experiences and

insights that the company has captured during its existence.

Summary

In this chapter, we learned about the role that data and databases

play in the context of information systems. Data is made up of

facts of the world. If you process data in a particular context, then

you have information. Knowledge is gained when information is

consumed and used for decision making. A database is an organized

collection of related data. Relational databases are the most widely

used type of database, where data is structured into tables and all

tables must be related to each other through unique identifiers. A

database management system (DBMS) is a software application that

is used to create and manage databases, and can take the form of

a personal DBMS, used by one person, or an enterprise DBMS that

can be used by multiple users. A data warehouse is a special form of

database that takes data from other databases in an enterprise and

organizes it for analysis. Data mining is the process of looking for

patterns and relationships in large data sets. Many businesses use

databases, data warehouses, and data-mining techniques in order to

produce business intelligence and gain a competitive advantage.

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Study Questions

1. What is the difference between data, information, and

knowledge?

2. Explain in your own words how the data component relates to

the hardware and software components of information

systems.

3. What is the difference between quantitative data and

qualitative data? In what situations could the number 42 be

considered qualitative data?

4. What are the characteristics of a relational database?

5. When would using a personal DBMS make sense?

6. What is the difference between a spreadsheet and a database?

List three differences between them.

7. Describe what the term normalization means.

8. Why is it important to define the data type of a field when

designing a relational database?

9. Name a database you interact with frequently. What would

some of the field names be?

10. What is metadata?

11. Name three advantages of using a data warehouse.

12. What is data mining?

13. In your own words, explain the difference between supervised

learning and unsupervised learning. Give an example of each

(not from the book).

Exercises

1. Review the design of the School database earlier in this

chapter. Reviewing the lists of data types given, what data

types would you assign to each of the fields in each of the

tables. What lengths would you assign to the text fields?

Chapter 4: Data and Databases | 97

2. Download Apache OpenOffice.org and use the database tool to

open the “Student Clubs.odb” file available here. Take some

time to learn how to modify the database structure and then

see if you can add the required items to support the tracking of

faculty advisors, as described at the end of the Normalization

section in the chapter. Here is a link to the Getting Started

documentation.

3. Using Microsoft Access, download the database file of

comprehensive baseball statistics from the website

SeanLahman.com. (If you don’t have Microsoft Access, you can

download an abridged version of the file here that is

compatible with Apache Open Office). Review the structure of

the tables included in the database. Come up with three

different data-mining experiments you would like to try, and

explain which fields in which tables would have to be analyzed.

4. Do some original research and find two examples of data

mining. Summarize each example and then write about what

the two examples have in common.

5. Conduct some independent research on the process of

business intelligence. Using at least two scholarly or

practitioner sources, write a two-page paper giving examples

of how business intelligence is being used.

6. Conduct some independent research on the latest

technologies being used for knowledge management. Using at

least two scholarly or practitioner sources, write a two-page

paper giving examples of software applications or new

technologies being used in this field.

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