Transcript ABET - Regis University: Academic Web Server for Faculty

CIS 480/BA 479: Managing
Technology for Business
Strategies
Week 2
Dr. Jesús Borrego
Regis University
1
scis.regis.edu ● [email protected]
Agenda
•
•
•
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2
Review of Homework 1
Group Project
Chapters 4, 5 and 6
Homework 2
Chapter 4
Ethical and Social Issues in Information Systems
3
Behavioral Targeting
• Problem: Need to efficiently target online ads.
• Solutions: Behavioral targeting allows businesses and
organizations to more precisely target desired
demographics.
• Google uses tracking files to monitor user activity on
thousands of sites; businesses monitor activity on their
own sites to better understand customers.
• Demonstrates IT’s role in organizing and distributing
information.
• Illustrates the ethical questions inherent in online
information gathering.
Understanding Ethical and Social Issues
Related to Systems
• Recent cases of failed ethical judgment in
business:
▫ Examples?
▫ In many, information systems used to bury
decisions from public scrutiny
• Ethics
▫ Principles of right and wrong that individuals,
acting as free moral agents, use to make choices to
guide their behaviors
Information systems and ethics
• Information systems raise new ethical
questions because they create
opportunities for:
▫ Intense social change, threatening existing
distributions of power, money, rights, and
obligations
▫ New kinds of crime
Ethical, social, and political Issues
• A model
▫ Society as a calm pond
▫ IT as rock dropped in pond, creating ripples of
new situations not covered by old rules
▫ Social and political institutions cannot respond
overnight to these ripples—it may take years to
develop etiquette, expectations, laws
 Requires understanding of ethics to make choices in
legally gray areas
Moral dimensions of the
information age:
• Information rights and obligations
• Property rights and obligations
• Accountability and control
• System quality
• Quality of life
Key technology trends that raise ethical
issues
• Doubling of computer power
▫ More organizations depend on computer systems for
critical operations.
• Rapidly declining data storage costs
▫ Organizations can easily maintain detailed databases on
individuals.
• Networking advances and the Internet
▫ Copying data from one location to another and accessing
personal data from remote locations are much easier.
Privacy Issues
▫ Advances in data analysis techniques
 Profiling
 Combining data from multiple sources to create
dossiers of detailed information on individuals
 Nonobvious relationship awareness (NORA)
 Combining data from multiple sources to find
obscure hidden connections that might help
identify criminals or terrorists
▫ Mobile device growth
 Tracking of individual cell phones
• NONOBVIOUS RELATIONSHIP
AWARENESS (NORA) NORA technology
Figure 4-2
can take
information
about people
from disparate
sources and
find obscure,
nonobvious
relationships.
It might
discover, for
example, that
an applicant
for a job at a
casino shares a
telephone
number with a
known
criminal and
Basic concepts for ethical analysis
• Responsibility:
▫ Accepting the potential costs, duties, and obligations for
decisions
• Accountability:
▫ Mechanisms for identifying responsible parties
• Liability:
▫ Permits individuals (and firms) to recover damages done to
them
• Due process:
▫ Laws are well-known and understood, with an ability to
appeal to higher authorities
Five-step ethical analysis
1. Identify and clearly describe the facts.
2. Define the conflict or dilemma and identify the
higher-order values involved.
3. Identify the stakeholders.
4. Identify the options that you can reasonably
take.
5. Identify the potential consequences of your
options.
Ethics in business and IT Videos
Take notes
• Chuck Gallagher on business ethics http://www.youtube.com/watch?v=gUJ00vNGCPE (14
min.)
• Professor Rick Shreve (Dartmouth’s Tuck School of
Business) –
▫ http://www.youtube.com/watch?v=R7sPDHrHj8c (10
min.)
▫ http://www.youtube.com/watch?v=9CPMlQUyr_Y (6
min.)
14
Candidate ethical principles
• Golden Rule
▫ Do unto others as you would have them do unto
you.
• Immanuel Kant’s Categorical Imperative
▫ If an action is not right for everyone to take, it is
not right for anyone.
• Descartes’ Rule of Change
▫ If an action cannot be taken repeatedly, it is not
right to take at all.
Candidate ethical principles (cont.)
• Utilitarian Principle
▫ Take the action that achieves the higher or greater
value.
• Risk Aversion Principle
▫ Take the action that produces the least harm or
potential cost.
• Ethical “No Free Lunch” Rule
▫ Assume that virtually all tangible and intangible
objects are owned by someone unless there is a
specific declaration otherwise.
Ethics in an Information Society
• Professional codes of conduct
▫ Promulgated by associations of professionals
 Examples: AMA, ABA, AITP, ACM
▫ Promises by professions to regulate themselves in
the general interest of society
• Real-world ethical dilemmas
▫ One set of interests pitted against another
 Example: right of company to maximize productivity
of workers versus workers right to use Internet for
short personal tasks
The Moral Dimensions of IS
• Information rights: privacy and freedom in the
Internet age
▫ Privacy:
 Claim of individuals to be left alone, free from
surveillance or interference from other individuals,
organizations, or state; claim to be able to control
information about yourself
▫ In the United States, privacy protected by:
 First Amendment (freedom of speech)
 Fourth Amendment (unreasonable search and
seizure)
 Additional federal statues (e.g., Privacy Act of 1974)
The Moral Dimensions of IS
• Fair information practices:
▫ Set of principles governing the collection and use of
information
 Basis of most U.S. and European privacy laws
 Based on mutuality of interest between record holder and
individual
 Restated and extended by FTC in 1998 to provide guidelines for
protecting online privacy
▫ Used to drive changes in privacy legislation




COPPA
Gramm-Leach-Bliley Act
HIPAA
Do-Not-Track Online Act of 2011
Fair Information Practices
• Principles:
▫ Notice/awareness (core principle)
 Web sites must disclose practices before collecting
data.
▫ Choice/consent (core principle)
 Consumers must be able to choose how information
is used for secondary purposes.
▫ Access/participation
 Consumers must be able to review and contest
accuracy of personal data.
Fair Information Practices (Cont’d)
• Security
▫ Data collectors must take steps to ensure accuracy,
security of personal data.
• Enforcement
▫ Must be mechanism to enforce FIP principles.
European Directive on Data Protection
• Companies must inform people information is
collected and disclose how it is stored and used.
• Requires informed consent of customer.
• EU member nations cannot transfer personal data to
countries without similar privacy protection (e.g.,
the United States).
• U.S. businesses use safe harbor framework.
▫ Self-regulating policy and enforcement that meets
objectives of government legislation but does not
involve government regulation or enforcement.
Internet challenges to privacy
• Cookies
▫ Identify browser and track visits to site
▫ Super cookies (Flash cookies)
• Web beacons (Web bugs)
▫ Tiny graphics embedded in e-mails and Web pages
▫ Monitor who is reading e-mail message or visiting site
• Spyware
▫ Surreptitiously installed on user’s computer
▫ May transmit user’s keystrokes or display unwanted ads
• Google services and behavioral targeting
HOW COOKIES IDENTIFY WEB VISITORS
Figure 4-3
Cookies are written by a Web site on a visitor’s hard drive. When the visitor returns to that Web site,
the Web server requests the ID number from the cookie and uses it to access the data stored by that
server on that visitor. The Web site can then use these data to display personalized information.
Moral Dimensions of IS
• The United States allows businesses to gather
transaction information and use this for other
marketing purposes.
▫ Opt-out vs. opt-in model
• Online industry promotes self-regulation over
privacy legislation.
• However, extent of responsibility taken varies:
▫ Complex/ambiguous privacy statements
▫ Opt-out models selected over opt-in
▫ Online “seals” of privacy principles
Technical solutions
•
•
•
•
E-mail encryption
Anonymity tools
Anti-spyware tools
Browser features
▫ “Private” browsing
▫ “Do not track” options
• Overall, few technical solutions
Mobile Technologies
• Why do mobile phone manufacturers (Apple,
Google, and BlackBerry) want to track where
their customers go?
• Do you think mobile phone customers should be
able to turn tracking off? Should customers be
informed when they are being tracked? Why or
why not?
• Do you think mobile phone tracking is a
violation of a person’s privacy
Property Rights: Intellectual Property
• Intellectual property: intangible property of any
kind created by individuals or corporations
• Three main ways that intellectual property is
protected:
▫ Trade secret: intellectual work or product
belonging to business, not in the public domain
▫ Copyright: statutory grant protecting intellectual
property from being copied for the life of the author,
plus 70 years
▫ Patents: grants creator of invention an exclusive
monopoly on ideas behind invention for 20 years
Intellectual Property Rights
• Challenges
▫ Digital media different from physical media (e.g.,
books)





Ease of replication
Ease of transmission (networks, Internet)
Difficulty in classifying software
Compactness
Difficulties in establishing uniqueness
• Digital Millennium Copyright Act (DMCA)
▫ Makes it illegal to circumvent technology-based
protections of copyrighted materials
Accountability, liability, control
• Computer-related liability problems
▫ If software fails, who is responsible?
 If seen as part of machine that injures or
harms, software producer and operator may
be liable.
 If seen as similar to book, difficult to hold
author/publisher responsible.
 What should liability be if software seen as
service? Would this be similar to telephone
systems not being liable for transmitted
messages?
System Quality
• Data quality and system errors
▫ What is an acceptable, technologically feasible
level of system quality?
 Flawless software is economically unfeasible.
▫ Three principal sources of poor system
performance:
 Software bugs, errors
 Hardware or facility failures
 Poor input data quality (most common source of
business system failure)
Quality of Life
• Equity, access, boundaries
▫ Negative social consequences of systems
 Balancing power: although computing power
decentralizing, key decision making remains
centralized
 Rapidity of change: businesses may not have enough
time to respond to global competition
 Maintaining boundaries: computing, Internet use
lengthens work-day, infringes on family, personal time
 Dependence and vulnerability: public and private
organizations ever more dependent on computer
systems
Moral Dimensions of IS
• Computer crime and abuse
▫ Computer crime: commission of illegal acts through use of
computer or against a computer system—computer may be object
or instrument of crime
▫ Computer abuse: unethical acts, not illegal
 Spam: high costs for businesses in dealing with spam
• Employment:
▫ Reengineering work resulting in lost jobs
• Equity and access—the digital divide:
▫ Certain ethnic and income groups in the United States less likely
to have computers or Internet access
Digital Divide
• What is it?
• How does information technology affect
socioeconomic disparities?
• Why is access to technology insufficient to
eliminate the digital divide?
• How serious a problem is the “new” digital
divide?
• Why is the digital divide problem an ethical
dilemma?
Chapter 5
IT Infrastructure and Emerging Technologies
35
IT Infrastructure
• Set of physical devices and software required to
operate enterprise
• Set of firmwide services including:
▫
▫
▫
▫
▫
▫
Computing platforms providing computing services
Telecommunications services
Data management services
Application software services
Physical facilities management services
IT management, education, and other services
• “Service platform” perspective
▫ More accurate view of value of investments
CONNECTION BETWEEN THE FIRM, IT INFRASTRUCTURE, AND BUSINESS CAPABILITIES
FIGURE 5-1
The services a firm is capable of providing to its customers, suppliers, and employees
are a direct function of its IT infrastructure. Ideally, this infrastructure should support
the firm’s business and information systems strategy. New information technologies
have a powerful impact on business and IT strategies, as well as the services that can be
provided to customers.
Evolution of IT Infrastructure
• General-purpose mainframe and
minicomputer era: 1959 to present
▫ 1958: IBM first mainframes introduced
▫ 1965: less expensive DEC minicomputers introduced
• Personal computer era: 1981 to present
▫ 1981: Introduction of IBM PC
▫ Proliferation in 80s, 90s resulted in growth of personal software
• Client/server era: 1983 to present
▫ Desktop clients networked to servers, with processing work split
between clients and servers
▫ Network may be two-tiered or multitiered (N-tiered)
▫ Various types of servers (network, application, Web)
Evolution of IT Infrastructure (Cont’d)
• Enterprise computing era: 1992 to present
▫ Move toward integrating disparate networks,
applications using Internet standards and
enterprise applications
• Cloud and mobile computing: 2000 to present
▫ Cloud computing: computing power and software
applications supplied over the Internet or other
network
 Fastest growing form of computing
STAGES IN IT INFRASTRUCTURE
EVOLUTION
Illustrated here
are the typical
computing
configurations
characterizing
each of the five
eras of IT
infrastructure
evolution.
FIGURE 5-2
STAGES IN IT INFRASTRUCTURE
EVOLUTION (cont.)
Illustrated here are
the typical
computing
configurations
characterizing
each of the five
eras of IT
infrastructure
evolution.
FIGURE 5-2
A MULTITIERED CLIENT/SERVER NETWORK (N-TIER)
FIGURE 5-3
In a multitiered client/server network, client requests for service are handled by different levels of
servers.
Technology drivers of infrastructure evolution
• Moore’s law and microprocessing power
▫ Computing power doubles every 18 months
▫ Nanotechnology:
 Shrinks size of transistors to size comparable
to size of a virus
• Law of Mass Digital Storage
▫ The amount of data being stored each year
doubles
MOORE’S LAW AND MICROPROCESSOR
PERFORMANCE
Packing more than
2 billion
transistors into a
tiny
microprocessor
has exponentially
increased
processing power.
Processing power
has increased to
more than
500,000 MIPS
(millions of
instructions per
second).
FIGURE 5-4
FALLING COST OF CHIPS
Packing more
transistors
into less
space has
driven down
transistor
cost
dramatically
as well as
the cost of
the products
in which
they are
used.
FIGURE 5-5
Nanotubes are tiny
tubes about
10,000 times
thinner than a
human hair.
They consist of
rolled up sheets
of carbon
hexagons and
have the
potential uses as
minuscule wires
or in ultrasmall
electronic
devices and are
very powerful
conductors of
electrical
current.
EXAMPLES OF NANOTUBES
FIGURE 5-6
THE COST OF STORING DATA DECLINES
EXPONENTIALLY 1950–2012
Since the first
magnetic
storage device
was used in
1955, the cost
of storing a
kilobyte of data
has fallen
exponentially,
doubling the
amount of
digital storage
for each dollar
expended every
15 months on
average.
FIGURE 5-7
Infrastructure Evolution
• Metcalfe’s Law and network economics
▫ Value or power of a network grows
exponentially as a function of the number
of network members
▫ As network members increase, more people
want to use it (demand for network access
increases)
Infrastructure Evolution
–Declining communication costs and the
Internet
• An estimated 2.3 billion people worldwide
have Internet access
• As communication costs fall toward a very
small number and approach 0, utilization
of communication and computing facilities
explodes
EXPONENTIAL DECLINES IN INTERNET COMMUNICATIONS COSTS
FIGURE 58
One reason for the growth in the Internet population is the rapid decline in Internet connection and
overall communication costs. The cost per kilobit of Internet access has fallen exponentially since 1995.
Digital subscriber line (DSL) and cable modems now deliver a kilobit of communication for a retail price
of around 2 cents.
Infrastructure Evolution
–Standards and network effects
• Technology standards:
–Specifications that establish the
compatibility of products and the ability to
communicate in a network
–Unleash powerful economies of scale and
result in price declines as manufacturers
focus on the products built to a single
standard
Infrastructure Components
• Seven main components
1. Computer hardware platforms
2. Operating system platforms
3. Enterprise software applications
4. Data management and storage
5. Networking/telecommunications platforms
6. Internet platforms
7. Consulting system integration services
THE IT INFRASTRUCTURE ECOSYSTEM
There are seven
major
components
that must be
coordinated
to provide the
firm with a
coherent IT
infrastructure
. Listed here
are major
technologies
and suppliers
for each
component.
FIGURE 5-9
Computer hardware platforms
• Client machines
▫ Desktop PCs, mobile devices—PDAs, laptops
• Servers
▫ Blade servers: ultrathin computers stored in racks
• Mainframes:
▫ IBM mainframe equivalent to thousands of blade
servers
• Top chip producers: AMD, Intel, IBM
• Top firms: IBM, HP, Dell, Sun Microsystems
Infrastructure Components
• Operating system platforms
▫ Operating systems
 Server level: 65% run Unix or Linux; 35% run
Windows
 Client level:
 90% run Microsoft Windows (XP, 2000, CE, etc.)
 Mobile/multitouch (Android, iOS)
 Cloud computing (Google’s Chrome OS)
• Enterprise software applications
▫ Enterprise application providers: SAP and Oracle
▫ Middleware providers: BEA
Infrastructure Components
• Data management and storage
– Database software:
• IBM (DB2), Oracle, Microsoft (SQL Server),
Sybase (Adaptive Server Enterprise), MySQL
– Physical data storage:
• EMC Corp (large-scale systems), Seagate,
Maxtor, Western Digital
– Storage area networks (SANs):
• Connect multiple storage devices on
dedicated network
Infrastructure Components
• Networking/telecommunications platforms
– Telecommunication services
• Telecommunications, cable, telephone company
charges for voice lines and Internet access
• AT&T, Verizon
– Network operating systems:
• Windows Server, Linux, Unix
– Network hardware providers:
• Cisco, Alcatel-Lucent, Nortel, Juniper Networks
Infrastructure Components
• Internet platforms
– Hardware, software, management services to
support company Web sites, (including Webhosting services) intranets, extranets
– Internet hardware server market: IBM, Dell,
Sun (Oracle), HP
– Web development tools/suites: Microsoft
(Expression Studio, .NET) Oracle-Sun (Java),
Adobe, Real Networks
BYOD
• The mobile digital platform
– Cell phones, smartphones (iPhone, Android,
and Blackberry)
• Data transmission, Web surfing, e-mail, and
IM duties
– Netbooks:
• Small lightweight notebooks optimized for
wireless communication and core tasks
– Tablets (iPad)
– Networked e-readers (Kindle and Nook)
Computer hardware platforms
• BYOD (Bring your own device)
▫ Allowing employees to use personal mobile
devices in workplace
• Consumerization of IT
▫ New information technology emerges in consumer
markets first and spreads to business
organizations
▫ Forces businesses and IT departments to rethink
how IT equipment and services are acquired and
managed
BYOD in the Enterprise
• What are the advantages and disadvantages of
allowing employees to use their personal
smartphones for work?
• What management, organization, and
technology factors should be addressed when
deciding whether to allow employees to use their
personal smartphones for work?
• Allowing employees to use their own
smartphones for work will save the company
money. Do you agree?
Platform Trends
• Grid computing
– Connects geographically remote computers into a
single network to combine processing power and
create virtual supercomputer
– Provides cost savings, speed, agility
• Virtualization
– Allows single physical resource to act as multiple
resources (i.e., run multiple instances of OS)
– Reduces hardware and power expenditures
– Facilitates hardware centralization
Platform Trends
• Cloud computing
– On-demand (utility) computing services obtained
over network
• Infrastructure as a service
• Platform as a service
• Software as a service
– Cloud can be public or private
– Allows companies to minimize IT investments
– Drawbacks: Concerns of security, reliability
– Hybrid cloud computing model
CLOUD COMPUTING PLATFORM
In cloud computing,
hardware and
software
capabilities are a
pool of
virtualized
resources
provided over a
network, often
the Internet.
Businesses and
employees have
access to
applications and
IT infrastructure
anywhere, at any
time, and on any
device.
Figure 5-10
Platform Trends
• Green computing
– Practices and technologies for manufacturing, using,
disposing of computing and networking hardware
• High performance, power-saving processors
– Multi-core processors
• Autonomic computing
– Industry-wide effort to develop systems that can
configure, heal themselves when broken, and protect
themselves from outside intruders
– Similar to self-updating antivirus software; Apple and
Microsoft both use automatic updates
Platform Trends
• Open-source software:
▫ Produced by community of programmers
▫ Free and modifiable by user
▫ Examples: Apache web server, Mozilla Firefox
browser, OpenOffice
• Linux
▫ Open-source OS
▫ Used in mobile devices, local area networks, Web
servers, high-performance computing
Software Trends
• Software for the Web
▫ Java:
 Object-oriented programming language
 Operating system, processor-independent
▫ HTML/HTML5
 Web page description language
 Specifies how text, graphics are placed on Web page
 HTML5 is latest evolution
 Includes animation and video processing functionality
previously provided by third party add-ons such as
Flash
Software Trends
• Web Services
▫ Software components that exchange information
using Web standards and languages
▫ XML: Extensible Markup Language
 More powerful and flexible than HTML
 Tagging allows computers to process data
automatically
Software Trends
• SOA: Service-oriented architecture
▫ Set of self-contained services that communicate
with each other to create a working software
application
▫ Software developers reuse these services in other
combinations to assemble other applications as
needed
 Example: an “invoice service” to serve whole firm for
calculating and sending printed invoices
▫ Dollar Rent A Car
 Uses Web services to link online booking system
with Southwest Airlines’ Web site
HOW DOLLAR RENT A CAR USES WEB SERVICES
FIGURE 5-11 Dollar Rent A Car uses Web services to provide a standard intermediate layer of software to “talk” to
other companies’ information systems. Dollar Rent A Car can use this set of Web services to link to
other companies’ information systems without having to build a separate link to each firm’s systems.
Software Trends
• Software outsourcing and cloud services
▫ Three external sources for software:
 Software packages and enterprise software
 Software outsourcing
 Contracting outside firms to develop software
 Cloud-based software services
 Software as a service (SaaS)
 Accessed with Web browser over Internet
 Service Level Agreements (SLAs): formal agreement
with service providers
CHANGING SOURCES OF FIRM SOFTWARE
Figure 5-12
In 2012, U.S. firms will spend more than $279 billion on software. About 35 percent of that ($98
billion) will originate outside the firm, either from enterprise software vendors selling firmwide
applications or individual application service providers leasing or selling software modules. Another 4
percent ($11 billion) will be provided by SaaS vendors as an online cloud-based service.
Contemporary Software Platform Trends
• Software outsourcing and cloud services (cont.)
– Mashups
• Combinations of two or more online applications,
such as combining mapping software (Google Maps)
with local content
– Apps
• Small pieces of software that run on the Internet, on
your computer, or on your cell phone
– iPhone, Android
• Generally delivered over the Internet
Management Issues
• Dealing with platform and infrastructure change
– As firms shrink or grow, IT needs to be flexible and
scalable
– Scalability:
• Ability to expand to serve larger number of users
– For mobile computing and cloud computing
• New policies and procedures for managing these
new platforms
• Contractual agreements with firms running clouds
and distributing software required
Management and Governance
–Who controls IT infrastructure?
–How should IT department be
organized?
• Centralized
– Central IT department makes decisions
• Decentralized
– Business unit IT departments make own decisions
–How are costs allocated between
divisions, departments?
IT Investment
• Amount to spend on IT is complex question
▫ Rent vs. buy, cloud computing
▫ Outsourcing
• Total cost of ownership (TCO) model
▫ Analyzes direct and indirect costs
▫ Hardware, software account for only about 20% of TCO
▫ Other costs: Installation, training, support, maintenance,
infrastructure, downtime, space, and energy
• TCO can be reduced
▫ Use of cloud services, greater centralization and
standardization of hardware and software resources
Chapter 6
Foundations of Business Intelligence: Databases
and Information Management
77
Data Organization
• File organization concepts
– Database: Group of related files
– File: Group of records of same type
– Record: Group of related fields
– Field: Group of characters as word(s) or number
• Describes an entity (person, place, thing on which we
store information)
• Attribute: Each characteristic, or quality, describing entity
– Example: Attributes DATE or GRADE belong to entity COURSE
THE DATA HIERARCHY
A computer system
organizes data in a hierarchy
that starts with the bit,
which represents either a 0
or a 1. Bits can be grouped to
form a byte to represent one
character, number, or
symbol. Bytes can be
grouped to form a field, and
related fields can be grouped
to form a record. Related
records can be collected to
form a file, and related files
can be organized into a
database.
FIGURE 6-1
Organizing Data in a Traditional File Environment
• Problems with the traditional file environment
(files maintained separately by different
departments)
– Data redundancy:
• Presence of duplicate data in multiple files
– Data inconsistency:
• Same attribute has different values
– Program-data dependence:
• When changes in program requires changes to data accessed
by program
– Lack of flexibility
– Poor security
– Lack of data sharing and availability
TRADITIONAL FILE PROCESSING
The use of a traditional
approach to file
processing encourages
each functional area in a
corporation to develop
specialized applications.
Each application requires
a unique data file that is
likely to be a subset of
the master file. These
subsets of the master file
lead to data redundancy
and inconsistency,
processing inflexibility,
and wasted storage
resources.
FIGURE 6-2
The Database Approach to Data Management
• Database
– Serves many applications by centralizing data and
controlling redundant data
• Database management system (DBMS)
– Interfaces between applications and physical data files
– Separates logical and physical views of data
– Solves problems of traditional file environment
•
•
•
•
Controls redundancy
Eliminates inconsistency
Uncouples programs and data
Enables organization to central manage data and data security
HUMAN RESOURCES DATABASE WITH MULTIPLE VIEWS
FIGURE 6-3
A single human resources database provides many different views of data, depending on the
information requirements of the user. Illustrated here are two possible views, one of interest to a
benefits specialist and one of interest to a member of the company’s payroll department.
The Database Approach to Data
Management
• Relational DBMS
– Represent data as two-dimensional tables
– Each table contains data on entity and attributes
• Table: grid of columns and rows
– Rows (tuples): Records for different entities
– Fields (columns): Represents attribute for entity
– Key field: Field used to uniquely identify each record
– Primary key: Field in table used for key fields
– Foreign key: Primary key used in second table as look-up field to
identify records from original table
Relational Database Tables
A relational database
organizes data in the form of
two-dimensional tables.
Illustrated here are tables for
the entities SUPPLIER and
PART showing how they
represent each entity and its
attributes. Supplier Number
is a primary key for the
SUPPLIER table and a
foreign key for the PART
table.
FIGURE 6-4
The Database Approach to Data Management
• Operations of a Relational DBMS
– Three basic operations used to develop useful
sets of data
• SELECT: Creates subset of data of all records that
meet stated criteria
• JOIN: Combines relational tables to provide user
with more information than available in individual
tables
• PROJECT: Creates subset of columns in table,
creating tables with only the information specified
THE THREE BASIC OPERATIONS OF A RELATIONAL DBMS
FIGURE 6-5
The select, join, and project operations enable data from two different tables to be combined and only
selected attributes to be displayed.
The Database Approach to Data Management
• Non-relational databases: “NoSQL”
▫
▫
▫
▫
More flexible data model
Data sets stored across distributed machines
Easier to scale
Handle large volumes of unstructured and structured
data (Web, social media, graphics)
• Databases in the cloud
▫ Typically, less functionality than on-premises DBs
▫ Amazon Relational Database Service, Microsoft SQL Azure
▫ Private clouds
The Database Approach to Data Management
• Capabilities of database management systems
– Data definition capability: Specifies structure of database
content, used to create tables and define characteristics of
fields
– Data dictionary: Automated or manual file storing definitions of
data elements and their characteristics
– Data manipulation language: Used to add, change, delete,
retrieve data from database
• Structured Query Language (SQL)
• Microsoft Access user tools for generating SQL
– Many DBMS have report generation capabilities for creating
polished reports (Crystal Reports)
MICROSOFT ACCESS DATA DICTIONARY FEATURES
FIGURE 6-6
Microsoft Access has a rudimentary data dictionary capability that displays information about the
size, format, and other characteristics of each field in a database. Displayed here is the information
maintained in the SUPPLIER table. The small key icon to the left of Supplier_Number indicates that
it is a key field.
EXAMPLE OF AN SQL QUERY
FIGURE 6-7
Illustrated here are the SQL statements for a query to select suppliers for parts 137 or 150. They
produce a list with the same results as Figure 6-5.
AN ACCESS QUERY
FIGURE 6-8
Illustrated here is how the query in Figure 6-7 would be constructed using Microsoft Access query
building
tools. It shows the tables, fields, and selection criteria used for the query.
The Database Approach to Data Management
• Designing Databases
– Conceptual (logical) design: abstract model from business perspective
– Physical design: How database is arranged on direct-access storage
devices
• Design process identifies:
– Relationships among data elements, redundant database elements
– Most efficient way to group data elements to meet business
requirements, needs of application programs
• Normalization
– Streamlining complex groupings of data to minimize redundant data
elements and awkward many-to-many relationships
AN UNNORMALIZED RELATION FOR ORDER
FIGURE 69
An unnormalized relation contains repeating groups. For example, there can be many parts and
suppliers for each order. There is only a one-to-one correspondence between Order_Number and
Order_Date.
NORMALIZED TABLES CREATED FROM ORDER
FIGURE 610
After normalization, the original relation ORDER has been broken down into four smaller relations.
The relation ORDER is left with only two attributes and the relation LINE_ITEM has a combined, or
concatenated, key consisting of Order_Number and Part_Number.
The Database Approach to Data Management
• Referential integrity rules
• Used by RDMS to ensure relationships between tables
remain consistent
• Entity-relationship diagram
▫ Used by database designers to document the data model
▫ Illustrates relationships between entities
– Caution: If a business doesn’t get data model
right, system won’t be able to serve business
well
AN ENTITY-RELATIONSHIP DIAGRAM
FIGURE 6-11 This diagram shows the relationships between the entities SUPPLIER, PART, LINE_ITEM, and
ORDER that might be used to model the database in Figure 6-10.
Using Databases to Improve Business
Performance and Decision Making
• Big data
• Massive sets of unstructured/semi-structured data
from Web traffic, social media, sensors, and so on
• Petabytes, exabytes of data
• Volumes too great for typical DBMS
• Can reveal more patterns and anomalies
Using Databases to Improve Business
Performance and Decision Making
• Business intelligence infrastructure
▫ Today includes an array of tools for separate systems,
and big data
• Contemporary tools:
▫
▫
▫
▫
▫
Data warehouses
Data marts
Hadoop
In-memory computing
Analytical platforms
Using Databases to Improve Business
Performance and Decision Making
• Data warehouse:
– Stores current and historical data from many core
operational transaction systems
– Consolidates and standardizes information for use across
enterprise, but data cannot be altered
– Provides analysis and reporting tools
• Data marts:
– Subset of data warehouse
– Summarized or focused portion of data for use by specific
population of users
– Typically focuses on single subject or line of business
COMPONENTS OF A DATA WAREHOUSE
A contemporary business
intelligence infrastructure
features capabilities and
tools to manage and
analyze large quantities
and different types of data
from multiple sources.
Easy-to-use query and
reporting tools for casual
business users and more
sophisticated analytical
toolsets for power users
are included.
FIGURE 6-12
Using Databases to Improve Business
Performance and Decision Making
• Hadoop
▫ Enables distributed parallel processing of big data
across inexpensive computers
▫ Key services
 Hadoop Distributed File System (HDFS): data storage
 MapReduce: breaks data into clusters for work
 Hbase: NoSQL database
▫ Used by Facebook, Yahoo, NextBio
Using Databases to Improve Business
Performance and Decision Making
• In-memory computing
▫ Used in big data analysis
▫ Use computers main memory (RAM) for data storage
to avoid delays in retrieving data from disk storage
▫ Can reduce hours/days of processing to seconds
▫ Requires optimized hardware
• Analytic platforms
▫ High-speed platforms using both relational and nonrelational tools optimized for large datasets
Using Databases to Improve Business
Performance and Decision Making
• Analytical tools: Relationships, patterns,
trends
– Tools for consolidating, analyzing, and providing
access to vast amounts of data to help users make
better business decisions
•
•
•
•
Multidimensional data analysis (OLAP)
Data mining
Text mining
Web mining
Using Databases to Improve Business
Performance and Decision Making
• Online analytical processing (OLAP)
– Supports multidimensional data analysis
• Viewing data using multiple dimensions
• Each aspect of information (product, pricing, cost, region,
time period) is different dimension
• Example: How many washers sold in East in June
compared with other regions?
– OLAP enables rapid, online answers to ad hoc queries
MULTIDIMENSIONAL DATA MODEL
The view that is showing is
product versus region. If you
rotate the cube 90 degrees,
the face that will show
product versus actual and
projected sales. If you rotate
the cube 90 degrees again,
you will see region versus
actual and projected sales.
Other views are possible.
FIGURE 6-13
Using Databases to Improve Business
Performance and Decision Making
• Data mining:
▫ Finds hidden patterns, relationships in datasets
 Example: customer buying patterns
▫ Infers rules to predict future behavior
▫ Types of information obtainable from data mining:





Associations
Sequences
Classification
Clustering
Forecasting
Using Databases to Improve Business
Performance and Decision Making
• Text mining
▫ Extracts key elements from large unstructured data
sets





Stored e-mails
Call center transcripts
Legal cases
Patent descriptions
Service reports, and so on
▫ Sentiment analysis software
 Mines e-mails, blogs, social media to detect opinions
Using Databases to Improve Business
Performance and Decision Making
• Web mining
– Discovery and analysis of useful patterns and
information from Web
– Understand customer behavior
– Evaluate effectiveness of Web site, and so on
– Web content mining
• Mines content of Web pages
– Web structure mining
• Analyzes links to and from Web page
– Web usage mining
• Mines user interaction data recorded by Web server
Using Databases to Improve Business
Performance and Decision Making
• Databases and the Web
– Many companies use Web to make some internal
databases available to customers or partners
– Typical configuration includes:
• Web server
• Application server/middleware/CGI scripts
• Database server (hosting DBMS)
– Advantages of using Web for database access:
• Ease of use of browser software
• Web interface requires few or no changes to database
• Inexpensive to add Web interface to system
LINKING INTERNAL DATABASES TO THE WEB
FIGURE 6-14 Users access an organization’s internal database through the Web using their desktop PCs and Web
browser software.
Managing Data Resources
• Establishing an information policy
▫ Firm’s rules, procedures, roles for sharing, managing,
standardizing data
▫ Data administration
 Establishes policies and procedures to manage data
▫ Data governance
 Deals with policies and processes for managing availability, usability,
integrity, and security of data, especially regarding government
regulations
▫ Database administration
 Creating and maintaining database
Managing Data Resources
• Ensuring data quality
– More than 25% of critical data in Fortune 1000
company databases are inaccurate or incomplete
– Redundant data
– Inconsistent data
– Faulty input
– Before new database in place, need to:
• Identify and correct faulty data
• Establish better routines for editing data once
database in operation
Managing Data Resources
• Data quality audit:
– Structured survey of the accuracy and level of
completeness of the data in an information system
• Survey samples from data files, or
• Survey end users for perceptions of quality
• Data cleansing
– Software to detect and correct data that are
incorrect, incomplete, improperly formatted, or
redundant
– Enforces consistency among different sets of data
from separate information systems
HW 2 – IT and Ethics
• There have been a number of headline examples recently
that have discussed the disregard for ethics in an
organization.
• The role of ethics in an organization is an important
component of the culture of an organization and impacts the
way Information Technology develops, manages, and
distributes data.
• Based on the readings this week as well as your own personal
experiences, write a three-to-five page paper on the topic of
IT and Ethics.
• Be sure to include a minimum of two resources in your
paper.
• You may use examples from your own work.
• Be sure to use APA style format for your paper
115
Questions?
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