Module 3 SLP will introduce the basic concepts of computer network.docx

Module 3 SLP will introduce the basic concepts of computer
networks. The IT infrastructure uses a mixture of computer
hardware from different vendors. Large and complex databases
that need central storage are found on mainframes or specialized
servers, whereas smaller databases and parts of large databases
are loaded on PCs and small servers. Client-server computing is
often used to distribute more processing power to the
desktop. The course materials take a look at the different types
of networks that exist, with the primary focus on the LAN. The
readings in computer networks continue with an introduction to
the concept of layers, which is central to understanding how
computer networks operate.
SLP Assignment Expectations
After reading the articles, please answer the following questions
and prepare a PPT presentation with 10-12 slides, excluding
cover slide and reference list slide.
What is the significance of telecommunications for
organizations and society? What is a telecommunications
system? What are the principle functions of all
telecommunications systems? Briefly describe the company
where these systems will be in place and then explain your
reasoning for its details.
Assignment Expectations
Your presentation will be evaluated on the following criteria:
Answers to the questions and the accompanying explanation
must be given in 10-12 slides excluding cover and reference
slides.
· Precision: You see what the module is all about and structure
your paper accordingly. You draw on a range of sources and
establish your understanding of the historical context of the
question. You carry out the exercise as assigned or carefully
explain the limitations that prevented your completing some
parts. (Running out of time isn’t generally considered an
adequate limitation).

· Clarity: Your answers are clear and show your good
understanding of the topic. You see what the module is all about
and structure your paper accordingly.
· Critical thinking: The paper incorporates your reactions,
examples, and applications of the material to business and
illustrates your reflective judgment and good understanding of
the concepts. It is important to read the "Required Reading" in
the Background material plus other sources you find relevant.
· Breadth and Depth: You provide informed commentary and
analysis—simply repeating what your sources say does not
constitute an adequate paper. The scope covered in your paper
is directly related to the questions of the assignment and the
learning outcomes of the module.
· Overall quality: You apply the professional language and
terminology of systems design and analysis correctly and in
context; you are familiar with this language and use it
appropriately. Your paper is well written and the references,
where needed, are properly cited and listed (refer to the
APA Purdue Online Writing Lab
athttps://owl.english.purdue.edu/owl/resource/560/01/) if you
are uncertain about formats or other issues.
11-*
Information Systems:
A Manager’s Guide to Harnessing Technology

11-*
This work is licensed under the
Creative Commons Attribution-Noncommercial-Share Alike 3.0
Unported License.
To view a copy of this license,
visit http://creativecommons.org/licenses/by-nc-sa/3.0/or send a
letter to
Creative Commons, 171 Second Street, Suite 300, San
Francisco, California, 94105, USA
11-*
Chapter 11
The Data Asset: Databases, Business Intelligence, and
Competitive Advantage
Learning ObjectivesUnderstand how increasingly standardized

data, access to third-party datasets, cheap, fast computing and
easier-to-use software are collectively enabling a new age of
decision makingBe familiar with some of the enterprises that
have benefited from data-driven, fact-based decision
makingUnderstand the difference between data and
informationKnow the key terms and technologies associated
with data organization and management
11-*
Learning ObjectivesUnderstand various internal and external
sources for enterprise dataRecognize the function and role of
data aggregators, the potential for leveraging third-party data,
the strategic implications of relying on externally purchased
data, and key issues associated with aggregators and firms that
leverage externally sourced dataKnow and be able to list the
reasons why many organizations have data that can’t be
converted to actionable informationUnderstand why
transactional databases can’t always be queried and what needs
to be done to facilitate effective data use for analytics and
business intelligence
11-*
Learning ObjectivesRecognize key issues surrounding data and
privacy legislationUnderstand what data warehouses and data
marts are, and the purpose they serveKnow the issues that need
to be addressed in order to design, develop, deploy, and
maintain data warehouses and data martsKnow the tools that are
available to turn data into informationIdentify the key areas
where businesses leverage data miningUnderstand some of the
conditions under which analytical models can fail
11-*

Learning ObjectivesRecognize major categories of artificial
intelligence and understand how organizations are leveraging
this technologyUnderstand how Wal-Mart has leveraged
information technology to become the world’s largest retailerBe
aware of the challenges that face Wal-Mart in the years ahead
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Learning ObjectivesUnderstand how Harrah’s has used IT to
move from an also-ran chain of casinos to become the largest
gaming company based on revenueName some of the technology
innovations that Harrah’s is using to help it gather more data,
and help push service quality and marketing program success
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IntroductionIncreasingly standardized corporate data, and
access to rich, third-party datasets, all leveraged by cheap, fast
computing and easier-to-use software, are enabling an age of
data-driven, fact-based decision makingBusiness intelligence
(BI): A term combining aspects of reporting, data exploration
and ad hoc queries, and sophisticated data modeling and
analysisAnalytics: A term describing the extensive use of data,
statistical and quantitative analysis, explanatory and predictive
models, and fact-based management to drive decisions and
actions
11-*
IntroductionData leverage and data-driven decision making is
important for obtaining competitive advantageIt can be a tough

slog getting an organization to the point where it has a data
asset that it can leverageIn many organizations data lies
dormant, spread across inconsistent formats and incompatible
systems, unable to be turned into anything of valueMany firms
have been shocked at the amount of work and complexity
required to pull together an infrastructure that empowers its
managers
11-*
Data, Information, and KnowledgeData: Raw facts and
figuresInformation: Data presented in a context so that it can
answer a question or support decision makingKnowledge:
Insight derived from experience and expertise
11-*
Understanding How is Data Organized: Key Terms and
TechnologiesDatabase: A single table or a collection of related
tablesDatabase management systems (DBMS): Sometimes called
“database software”; software for creating, maintaining, and
manipulating dataStructured query language (SQL): A language
used to create and manipulate databasesDatabase administrator
(DBA): Job title focused on directing, performing, or
overseeing activities associated with a database or set of
databasesIncludes database design, creation, implementation,
maintenance, backup and recovery, policy setting and
enforcement, and security
11-*
TechnologiesKey concepts that all managers should know:A

table or file refers to a list of dataA database is either a single
table or a collection of related tablesA column or field defines
the data that a table can holdA row or record represents a single
instance of whatever the table keeps track ofA key is the field
used to relate tables in a database
11-*
TechnologiesTable or file: A list of data, arranged in columns
(fields) and rows (records)Column or field: A column in a
database table. Columns represent each category of data
contained in a record (e.g., first name, last name, ID number,
data of birth)
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TechnologiesRow or record: A row in a database table. Records
represent a single instance of whatever the table keeps track of
(e.g., student, faculty, course title)Key: A field or combination
of fields used to uniquely identify a record, and to relate
separate tables in a database. Examples include social security
number, customer account number, or student IDRelational
database: The most common standard for expressing databases,
whereby tables (files) are related based on common keys
11-*
Where Does Data Come From?For organizations that sell
directly to their customers, transaction processing systems
represent a fountain of potentially insightful dataTransaction
processing systems (TPS): A system that records a transaction

(some form of business-related exchange), such as a cash
register sale, ATM withdrawal, or product returnTransaction:
Some kind of business exchangeThe cash register is the primary
source that feeds data to the TPSTPS can generate a lot of bits,
it’s sometimes tough to match this data with a specific customer
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Where Does Data Come From?Enterprise software (CRM, SCM,
and ERP)Firms set up systems to gather additional data beyond
conventional purchase transactions or Web site monitoring
CRM or customer relationship management systems are used to
empower employees to track and record data at nearly every
point of customer contactSupply chain management (SCM) and
enterprise resource planning (ERP) systems touch every aspect
of the value chain
11-*
Where Does Data Come From?SurveysFirms supplement
operational data with additional input from surveys and focus
groupsDirect surveys can tell you what your cash register
can’tMany CRM products have survey capabilities that allow
for additional data gathering at all points of customer contact
11-*
Where Does Data Come From?External sourcesIf your firm has
partners that sell products for you, then you’ll likely rely
heavily on data collected by othersData bought from sources
available to all might not yield competitive advantage on its
own, but it can provide key operational insight for increased

efficiency and cost savings
11-*
Data Rich, Information PoorMany organizations are data rich
but information poorFactors holding back information
advantageLegacy system: Older information systems that are
often incompatible with other systems, technologies, and ways
of conducting businessMost transactional databases aren’t set
up to be simultaneously accessed for reporting and analysis
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Data Warehouses and Data MartsData warehouses: A set of
databases designed to support decision making in an
organizationStructured for fast online queries and
explorationMay aggregate enormous amounts of data from many
different operational systemsData marts: A database or
databases focused on addressing the concerns of a specific
problem (e.g., increasing customer retention, improving product
quality) or business unit (e.g., marketing, engineering)
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Data Warehouses and Data MartsMarts and warehouses may
contain huge volumes of dataLarge data warehouses can cost
millions and take years to buildLarge-scale data analytics
projects should start with a clear vision with business-focused
objectives
11-*

Figure 11.2 - Information systems supporting operations (such
as TPS) are typically separate, and “feed” information systems
used for analytics (such as data warehouses and data marts)
11-*
Data Warehouses and Data MartsOnce a firm has business goals
and hoped-for payoffs clearly defined, it can address the
broader issues needed to design, develop, deploy, and maintain
its system:Data relevanceData sourcingData quantity and
qualityData hostingData governance
11-*
The Business Intelligence ToolkitQuery and reporting
toolsCanned reports: Reports that provide regular summaries of
information in a predetermined formatAd hoc reporting tools:
Tools that put users in control so that they can create custom
reports on an as-needed basis by selecting fields, ranges,
summary conditions, and other parametersDashboards: A heads-
up display of critical indicators that allow managers to get a
graphical glance at key performance metrics
11-*
The Business Intelligence ToolkitOnline analytical processing
(OLAP): A method of querying and reporting that takes data
from standard relational databases, calculates and summarizes
the data, and then stores the data in a special database called a
data cubeData cube: A special database used to store data in
OLAP reporting
11-*

Data MiningData mining is the process of using computers to
identify hidden patterns in, and to build models from, large data
setsKey areas where businesses are leveraging data mining
include:Customer segmentationMarketing and promotion
targetingMarket basket analysis
11-*
Data MiningCollaborative filteringCustomer churnFraud
detectionFinancial modelingHiring and promotionFor data
mining to work, two critical conditions need to be present:The
organization must have clean, consistent dataThe events in that
data should reflect current and future trends
11-*
Data MiningProblems associated with the use of bad
data:Wrong estimates from bad data leaves the firm
overexposed to riskProblem of historical consistency:Computer-
driven investment models are not very effective when the
market does not behave as it has in the pastOver-engineer Build
a model with so many variables that the solution arrived at
might only work on the subset of data you’ve used to create itA
pattern is uncovered but determining the best choice for a
response is less clear
11-*
Data MiningA data mining and business analytics team should
possesses three critical skills:Information
technologyStatisticsBusiness knowledge

11-*
Artificial IntelligenceData Mining has its roots in a branch of
computer science known as artificial intelligence (or AI)The
goal of AI is create computer programs that are able to mimic or
improve upon functions of the human brain
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Artificial IntelligenceNeural network: An AI system that
examines data and hunts down and exposes patterns, in order to
build models to exploit findingsExpert systems: AI systems that
leverages rules or examples to perform a task in a way that
mimics applied human expertiseGenetic algorithms: Model
building techniques where computers examine many potential
solutions to a problem, iteratively modifying various
mathematical models, and comparing the mutated models to
search for a best alternative
11-*
Data Asset in Action: Technology and the Rise of Wal-
MartWal-Mart demonstrates how a physical product retailer can
create and leverage a data asset to achieve world-class supply
chain efficiencies targeted primarily at driving down costsWal-
Mart is the largest retailer in the worldIt’s key source of
competitive advantage is scale
11-*
A Data-Driven Value ChainThe Wal-Mart efficiency dance

starts with a proprietary system called Retail LinkRetail Link
records the sale and automatically triggers inventory reordering,
scheduling, and deliveryBack-office scanners keep track of
inventory as supplier shipments comes inWal-Mart has been a
catalyst for technology adoption among its suppliers
11-*
Data Mining ProwessWal-Mart mines its data to get its product
mix right under all sorts of varying environmental conditions,
protecting the firm from a retailer’s twin nightmares: too much
inventory, or not enoughData mining helps the firm tighten
operational forecasts, helping it to predict thingsData drives the
organization, with mined reports forming the basis of weekly
sales meetings and executive strategy sessions
11-*
*
Sharing Data, Keeping SecretsWal-Mart shares sales data with
relevant suppliersWal-Mart has stopped sharing data with
information brokers Other aspects of the firm’s technology
remain under wrapsWal-Mart custom builds large portions of its
information systems to keep competitors off its trail
11-*
Challenges AboundAs a mature business, Wal-Mart faces a
problemIt needs to find huge markets or dramatic cost savings
in order to boost profits and continue to move its stock price

higherCriticisms against Wal-MartAccusations of sub par wages
and remains a magnet for union activistsPoor labor conditions at
some of the firm’s contract manufacturersWal-Mart demand
prices so aggressively low that suppliers end up cannibalizing
their own sales at other retailers
11-*
Challenges AboundThe firm’s data warehouse wasn’t able to
foretell the rise of Target and other up-market
discountersAnother major challenge - Tesco methodically
attempts to take its globally honed expertise to U.S. shores
11-*
Data Asset in Action: Harrah’s Solid Gold CRM for the Service
SectorHarrah’s Entertainment provides an example of
exceptional data asset leverage in the service sector, focusing
on how this technology enables world-class service through
customer relationship managementHarrah’s has leveraged its
data-powered prowess to move from an also-ran chain of
casinos to become the largest gaming company by revenue
11-*
Collecting DataHarrah’s collects customer data on everything
you might do at their propertiesThe data is then used to track
your preferences and to size up whether you’re the kind of
customer that’s worth pursuing
11-*

Collecting DataThe ace in Harrah’s data collection hole is its
Total Rewards loyalty card systemThe system is constantly
being enhanced by an IT staff of seven hundred, with an annual
budget in excess of one hundred million dollarsIt is an opt-in
loyalty program, but customers consider the incentives to be so
good that the card is used by some 80 percent of Harrah’s
patrons
11-*
Who are the Most Valuable Customers?With detailed historical
data at hand Harrah’s can make fairly accurate projections of
customer lifetime value (CLV)Customer lifetime value (CLV):
The present value of the likely future income stream generated
by an individual purchaserThe firm tracks over ninety
demographic segments, and each responds differently to
different marketing approaches
11-*
Who are the Most Valuable Customers?Identifying segments
and figuring out how to deal with each involves:An iterative
model of mining the data to identify patternsCreating a
hypothesis, then testing that hypothesis against a control
groupTurning to analytics to statistically verify the
outcomeFrom its data, Harrah’s realized that most of its profits
came from:LocalsCustomers forty-five years and older
11-*
Data Driven Service: Get Close (But Not Too Close) to Your
CustomersHarrah’s identifies the high value customers and
provides special attention to themCustomers could obtain

reserved tables and special offersIt monitors even gamblers
suffering unusual losses, and provide feel-good offers to
themThe firm’s CRM effort monitors any customer behavior
changesCustomers come back to Harrah’s because they feel that
those casinos treat them better than the competition
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Data Driven Service: Get Close (But Not Too Close) to Your
CustomersHarrah’s focus on service quality and customer
satisfaction are embedded into its information systems and
operational proceduresEmployees are measured on metrics that
include speed and friendliness and are compensated based on
guest satisfaction ratingsThe process effectively changed the
corporate culture at Harrah’s from an every-property-for-itself
mentality to a collaborative, customer-focused
enterpriseHarrah’s is keenly sensitive to respecting consumer
dataSome of its efforts to track customers have misfired
11-*
InnovationHarrah’s is constantly tinkering with new innovations
that help it gather more data and help push service quality and
marketing program successInteractive bill boards, RFID-enabled
poker chips and under-table RFID readers, incorporation of
drink ordering to gaming machines, and touch-screen and
sensor-equipped tabletop are examples of such innovations
11-*
StrategyThe data is the major competitive advantage for
Harrah’sThe data advantage creates intelligence for a high-
quality and highly personal customer experienceThe data gives

the firm a service differentiation edgeThe loyalty program
represents a switching costThe firm’s technology has been
pretty tough for others to match and the firm holds many patents
11-*
ChallengesGaming is a discretionary spending item, and when
the economy tanks, gambling is one of the first things
consumers will cutHarrah’s holds twenty-four billion dollars in
debt from expansion projects and the buyoutThe firm is now in
a position many consider risky due to debt assumed as part of
an overly optimistic buyout
11-*
1-*
Information Systems:
A Manager’s Guide to Harnessing Technology
1-*
This work is licensed under the
Creative Commons Attribution-Noncommercial-Share Alike 3.0
Unported License.
To view a copy of this license,

visit http://creativecommons.org/licenses/by-nc-sa/3.0/or send a
letter to
Creative Commons, 171 Second Street, Suite 300, San
Francisco, California, 94105, USA
1-*
Chapter 12
A Manager’s Guide to The Internet and Telecommunications
1-*
Learning ObjectivesDescribe how the technologies of the
Internet combine to answer the questions: What are you looking
for? Where is it? And how do we get there?Interpret a URL,
understand what hosts and domains are, describe how domain
registration works, describe cybersquatting, and give examples
of conditions that constitute a valid and invalid domain-related
trademark dispute
1-*
Learning ObjectivesDescribe certain aspects of the Internet
infrastructure that are fault tolerant and supports load balancing
Discuss the role of hosts, domains, IP addresses, and the DNS
in making the Internet workUnderstand the layers that make up
the Internet – application protocol, transmission control
protocol, and internet protocol – and describe why each is
important

1-*
Learning ObjectivesDiscuss the benefits of Internet architecture
in general, and TCP/IP in particularName applications that
should use TCP, and others that might use UDP Understand
what a router does, and the role these devices play in
networking
1-*
Learning ObjectivesConduct a traceroute and discuss output,
demonstrating how Internet interconnections work in getting
messages from point to pointAppreciate why mastery of Internet
infrastructure is critical to modern finance, and be able to
discuss the risks in automated trading systemsDescribe VoIP,
and contrast circuit vs. packet switching, along with
organizational benefits and limitations of each
1-*
Learning ObjectivesUnderstand the last mile problem, and be
able to discuss the pros and cons of various broadband
technologies including DSL, cable, fiber, and various wireless
offerings Describe 3G and 4G systems, listing major
technologies and their backers Understand the issue of net
neutrality and put forth arguments supporting or criticizing the
concept
1-*
Figure 12.1 – The Internet is a network of networks, and these
networks are connected togetherThe Internet is a network of

millions of networks
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Figure 12.2 – Anatomy of a Web Address
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The Web AddressHypertext transfer protocol (http) - application
transfer protocol that allows web browsers and web servers to
communicateA domain name represents an organization and a
host refers to public services offered by that organizationHost
and domain names are case-insensitivePath maps to folder
location where file is stored on serverPath and filenames are
case sensitiveFilename refers to name of file stored on server
Item Number: 101783940
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Host and Domain Names: A Bit More Complex Than That A
domain name represents an organizationHosts are public
services offered by that organizationLoad Balancing:
Distributing a computing or networking workload across
multiple systems in order to avoid congestion and slow
performanceFault Tolerant: Systems that are capable of
continuing operation even if a component fails
1-*
I Want My Own Domain One can register a domain name,
paying for a renewable right to use that domain nameDomain
name registration is handled on a first-come, first-served basis

and all registrars share registration data to ensure that no two
firms gain rights to the same nameCybersquatting: Acquiring a
domain name that refers to a firm, individual, product, or
trademark, with the goal of exploiting it for financial gain
1-*
IP Addresses and the Domain Name SystemEvery device
connected to the Internet has an identifying address called the
Internet Protocol (IP) addressThe domain name service is
hierarchical system of nameservers that maps host-domain name
combinations to IP addressesThe cache is a temporary storage
space that speeds up IP address mapping by avoiding
nameserver visits
1-*
Figure 12.3 – When your Computer needs to find the IP address
for a host or domain name, it sends a message to a DNS
resolver, which looks up the IP address starting at the root
nameserver
1-*
The Internet is Almost FullInefficient allocation of IP addresses
and exploding number of Internet connected devices means that
we’re running out of IP addresses Shifting to a new IP scheme
such as IPv6 increases the possible address space to a new
theoretical limit of 2128 addresses

1-*
TCP/IP – The Internet’s Secret Sauce The Internet Protocol
Suite consists of:Transmission Control Protocol (TCP)Internet
Protocol (IP)TCP works at both ends of Internet
communications to ensure perfect copies of messages are sent
IP is a routing protocol in charge of forwarding packets on the
InternetRouters are computing devices that connect networks
and exchange data between them
1-*
Figure 12.4 – TCP/IP in Action
1-*
RoutersRouters are special computing devices that forward
packets from one location to the nextRouters are typically
connected with more than one outbound path, so that in case one
path becomes unavailable, an alternate path can be used
1-*
UDP: TCP’s Faster, Less Reliable Sibling TCP is a perfectionist
and this is essential for web transmissions, e-mail, and
application downloads Streaming media applications like
Internet voice chat and video conferencing require sacrificing of
perfection for speed User Datagram Protocol (UDP) works as a
TCP stand-in speed is needed and quality has to be sacrificed
1-*
VoIPOld phone systems use circuit switching for a dedicated

connection between two entitiesInternet networks are packet
switched and conversations are sliced into packets and squeezed
into smaller spacesVoIP allows voice and phone systems to
become an application traveling over the Internet
1-*
Finance has a Need for Speed Electronic trading systems
leverage data mining and other techniques to crunch massive
volumes of data and discover exploitable market patternsModels
are then run against real-time data and executed the instant a
trading opportunity is detectedSystems that run on their own
can move many billions instantly, and the actions of one system
may cascade, triggering actions by others
1-*
Watching the Packet Path via Traceroute Traceroute sends
clusters of three packets starting at first router connected to a
computer, then the next, and so on, building out paths packets
take to their destinationSome networks block traceroute because
hackers have used the tool to probe a network to figure out how
to attack an organization
1-*
What Connects the Routers and Computers?Computers are
connected to the Internet by:Copper cable, for short
distancesFiber optic lines, for long distancesWireless TCP/IP is
not dependent on transmission mediaMost Internet
communications are carried out via a combination of
transmission media
Item number: 92041959

1-*
Last Mile: Faster Speed, Broader Access The Internet
Backbone, made of fiber optic lines, is very fastAmdahl’s law
sates that a system’s speed is determined by its slowest
component or the last mile High-speed last mile technologies
are often referred to as Broadband Internet AccessVarious
technology upgrades are happening to speed up last mile
connectivity
1-*
Cable BroadbandMajority of domestic broadband connections
are through copper cable technologyCoaxial copper cables have
shielding to reduce electrical interferenceSignals travel longer
distances without degrading and at significant speedsFiber/optic
hybrid based networks are expensive, but offer higher speeds
1-*
DSL – Phone Company CopperDSL technology uses copper wire
phone companies have already run into homesUnlike cable, DSL
uses standard copper wiring without shieldingSignals degrade
with distance from phone company officesDSL technology is
popular in Europe and Asia owing to densely populated
citiesDSL connections are infeasible in the U.S. where cities are
sparsely populated
1-*
Fiber – A Light-filled Glass Pipe to your Doorstep FTTH or

Fiber to the Home is the fastest last mile technology
aroundFTTH networks need to be built from scratch as they do
not have preexisting infrastructureHowever, FTTH can be
profitable as it supports a wide range of servicesMany ISPs like
Google and Verizon have made multibillion investments in
FTTH for experimental and business reasons, respectively
1-*
WirelessMobile wireless service is provided to customers via
cell towersWith boom in sales of smart phones, bandwidth
crunch is becoming a serious concern for ISPsWireless networks
are transitioning from third generation (3G) to fourth generation
(4G)3G networks are slower than 4G and offer a lesser range of
services
1-*
3G standards3G standards are divided along two camps:Global
System for Mobile Communications (GSM)Code Division
Multiple Access (CDMA)The GSM standard is the most used
around the worldCDMA is limited by its inability to support
voice and data communication at the same time
1-*
4G standards4G standards are divided along the lines of:Long
Term Evolution (LTE)Worldwide Interoperability for
Microwave Access (WiMax)DSL, cable, and fiber firms could
be affected by 4G implementations4G offers them option of
entering mobile phone business and offer a wider range of

servicesIf speeds of 4G networks increase, more users could
switch from cable, DSL, and fiber to wireless Internet access
1-*
Satellite WirelessEarly satellite based telecommunications
services suffered from problems such as:Download-only
capabilityRequired expensive and bulky equipmentHigh
latencyO3b networks has offered to provide fiber-quality
broadband accessO3b plans to use a network of middle earth
orbit satellites to reduce latencyIf O3b’s efforts are successful,
it could transform the broadband industry
1-*
Wi-Fi and other hotspotsComputer and mobile devices have
Wireless Fidelity antennas built into their chipsetsTo connect to
the Internet, a device needs to be within range of a base station
or hotspotCell coverage is often limited due to lack of service
towersFentocells are being offered to improve wireless
reception
1-*
Net Neutrality- What’s Fair?Net neutrality is the principle that
all Internet traffic should be treated equallyMany ISPs offer
varying coverage, depending on service used and bandwidth
consumedInternet firms say it is vital to maintain the openness
of the Internet Telecommunications firms say they should be
able to limit access to services that overtax their networks
Another concern for service providers is ever-increasing
demand for greater bandwidth

big data
A general term used to
describe massive amount of
data available to today’s
managers. Big data are often
unstructured and are too big
and costly to easily work
through use of conventional
databases, but new tools are
making these massive
datasets available for analysis
and insight.
business intelligence (BI)
A term combining aspects of
reporting, data exploration
and ad hoc queries, and
sophisticated data modeling
and analysis.
analytics
A term describing the
extensive use of data,
statistical and quantitative
analysis, explanatory and
predictive models, and
fact-based management to
drive decisions and actions.
C H A P T E R 1 1

The Data Asset: Databases,
Business Intelligence, and
Competitive Advantage
1. INTRODUCTION
L E A R N I N G O B J E C T I V E S
1. Understand how increasingly standardized data, access to
third-party data sets, cheap, fast
computing and easier-to-use software are collectively enabling a
new age of decision making.
2. Be familiar with some of the enterprises that have benefited
from data-driven, fact-based de-
cision making.
The planet is awash in data. Cash registers ring up transactions
worldwide. Web browsers leave a trail
of cookie crumbs nearly everywhere they go. And with radio
frequency identification (RFID), invent-
ory can literally announce its presence so that firms can
precisely journal every hop their products
make along the value chain: “I’m arriving in the warehouse,”
“I’m on the store shelf,” “I’m leaving out
the front door.”
A study by Gartner Research claims that the amount of data on
corporate hard drives doubles
every six months,[1] while IDC states that the collective
number of those bits already exceeds the num-
ber of stars in the universe.[2] Wal-Mart alone boasts a data
volume well over 125 times as large as the
entire print collection of the U.S. Library of Congress, and
rising.[3] You’ll hear managers today broadly
refer to this torrent of bits as “Big Data.”

And with this flood of data comes a tidal wave of opportunity.
Increasingly standardized corporate
data, and access to rich, third-party data sets—all leveraged by
cheap, fast computing and easier-to-use
software—are collectively enabling a new age of data-driven,
fact-based decision making. You’re less
likely to hear old-school terms like “decision support systems”
used to describe what’s going on here.
The phrase of the day is business intelligence (BI), a catchall
term combining aspects of reporting,
data exploration and ad hoc queries, and sophisticated data
modeling and analysis. Alongside business
intelligence in the new managerial lexicon is the phrase
analytics, a term describing the extensive use
of data, statistical and quantitative analysis, explanatory and
predictive models, and fact-based manage-
ment to drive decisions and actions.[4]
The benefits of all this data and number crunching are very real,
indeed. Data leverage lies at the
center of competitive advantage we’ve studied in the Zara,
Netflix, and Google cases. Data mastery has
helped vault Wal-Mart to the top of the Fortune 500 list. It
helped Harrah’s Casino Hotels grow to be
twice as profitable as similarly sized Caesars and rich enough to
acquire this rival (Harrah’s did decide
that it liked the Caesars name better and is now known as
Caesars Entertainment). And data helped
Capital One find valuable customers that competitors were
ignoring, delivering ten-year financial per-
formance a full ten times greater than the S&P 500. Data-driven
decision making is even credited with
helping the Red Sox win their first World Series in eighty-three
years and with helping the New Eng-
land Patriots win three Super Bowls in four years. To quote

from a BusinessWeek cover story on analyt-
ics, “Math Will Rock Your World!”[5]
Sounds great, but it can be a tough slog getting an organization
to the point where it has a leverag-
able data asset. In many organizations data lies dormant, spread
across inconsistent formats and in-
compatible systems, unable to be turned into anything of value.
Many firms have been shocked at the
Personal PDF created exclusively for Dr. Mina Richards
([email protected])
amount of work and complexity required to pull together an
infrastructure that empowers its man-
agers. But not only can this be done, it must be done. Firms that
are basing decisions on hunches aren’t
managing; they’re gambling. And today’s markets have no
tolerance for uninformed managerial dice
rolling.
While we’ll study technology in this chapter, our focus isn’t as
much on the technology itself as it is
on what you can do with that technology. Consumer products
giant P&G believes in this distinction so
thoroughly that the firm renamed its IT function as “Information
and Decision
Solution
s.”[6]

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