Queen Mary University of London Programming Case Study

IT for Management: On-Demand Strategies forPerformance, Growth, and Sustainability
Twelfth Edition
Turban, Pollard, Wood
Chapter 2
Information Systems, IT Infrastructure, and
Cloud
IS Concepts and
Classifications
IT
Infrastructure,
IT Architecture,
and Enterprise
Architecture
Virtualization
and Virtual
Machines
Data Centers
and Cloud
Computing
Learning Objectives (1 of 4)
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2
IS Concepts and Classification


Information system (IS) is a combination of
information technology and people’s activities using
technology to support business processes, operations,
management, and decision-making at different levels
of the organization.
Technology supports organizations and almost every
business unit within an organization.
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Figure 2.1 IPOS Cycle
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Figure 2.2:
Components
of an
Information
System
Data, Information, Knowledge, & Wisdom
• Data describes products, customers, events, activities, and
transactions that are recorded, classified, and stored.
• Information is data that have been processed, organized, or put
into context with meaning and value to the recipient.
• Knowledge applies understanding, experience, accumulated
learning, and expertise to current problem.
o
o
Explicit knowledge is the most basic form of knowledge and is easy to
communicate, store, and distribute
Tacit knowledge is the opposite of explicit knowledge and is difficult to
transfer to others. It is personal, context-specific, and experiential.
• Wisdom is a collection of values, ethics, moral codes, and prior
experiences that form an evaluated understanding or
commonsense judgment.
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Figure 2.3:
Examples of
Data,
Information,
Knowledge,
and Wisdom
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Figure 2.4 Data processing in the IPOS cycle
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Transaction Processing Systems (TPS)
Transaction processing system (TPS) is an information
system that collects, monitors, stores, processes, and
distributes specific types of data input from ongoing
transactions.
• Internal transactions: originate or occur within the
organization (payroll, purchases, etc.)
• External transactions: originate outside the
organization (customers, suppliers, etc.)
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Real-Time Versus Batch Processing
• Real-time processing or OLTP: processes each
transaction as it occurs
• Batch Processing: collects all transactions for a time
period, then processes the data at a predetermined
time, such as hourly, daily, or weekly
• Batch processing costs less than OLTP, but may be
inaccurate from update delays
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Management Information Systems (MIS)
• General-purpose reporting systems that provide
reports to managers for tracking operations,
monitoring, and control.
Periodic: reports created or run according to a pre-set
schedule.
o Exception: generated only when something is outside the
norm.
o
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Decision Support Systems (DSS) (1 of 2)
• A knowledge-based system used by senior managers to
facilitate the creation of knowledge and allow its
integration into the organization
o
Ad hoc or on demand reports are unplanned reports.
• Support unstructured and unstructured decisions with
the following characteristics:
Easy-to-use interactive interface
o Models or formulas that enable sensitivity analysis
o Data from multiple sources
o
• Can be used for open-ended What-if analysis and more
structured Goal-seeking
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Executive Information Systems (EIS)
• Strategic-level information systems that help executives
and senior managers analyze the environment in which
the organization exists
• Used to identify log-term trends and plan appropriate
actions
• Weakly structured data from both internal and external
sources
• Designed to be easily operated by executives
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IS Concepts and
Classifications
IT
Infrastructure,
IT Architecture,
and Enterprise
Architecture
Virtualization
and Virtual
Machines
Data Centers
and Cloud
Computing
Learning Objectives (2 of 4)
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Figure 2.9: Comparing IT infrastructure, IT architecture, and EA
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IT Infrastructure
• Inventory of the physical IT devices that an organization
owns and operates
• Describes organization’s entire collection of hardware,
software, networks, data centers, facilities and related
equipment
• Does not include people or process components of an
IS
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IT Architecture
• Guides the process of planning, acquiring, building,
modifying, interfacing and deploying IT resources in a
single department within an organization
• Should offer a way to systematically identify
technologies that work together to satisfy the needs of
the departments’ users
• Blueprint for how future technology acquisitions and
deployment will take place
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Enterprise architecture (EA)
• A conceptual blueprint that defines the structure and
operation of an organization’s strategy, information,
processes, and IT assets
• The EA adds value to an organization in that it can
provide the basis for organizational change just as
architectural plans guide a construction project.
• Solves two critical challenges: where an organization is
going and how it will get there.
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Measuring EA Success: KPIs
• Key Performance Indicators (KPIs) are a set of
quantifiable measures used to evaluate factors that are
critical to the success of an organization.
• KPIs help reduce the complex nature of EA
performance to a small number of understandable
measures such as capabilities, operational
performance, project performance, and financial
performance.
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EA and Sustainability
• Strategic Focus
IT systems’ complexity
o Poor business alignment
o
• Business and IT Benefits of EA
Cuts IT costs; increases productivity with information, insight,
and ideas
o Determines competitiveness, flexibility, and IT economics
o Aligns IT capabilities with business strategy to grow, innovate,
and respond to market demands
o Reduces risk of buying or building systems and enterprise
apps
o
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EA Components
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IS Concepts and
Classifications
IT
Infrastructure,
IT Architecture,
and Enterprise
Architecture
Virtualization
and Virtual
Machines
Data Centers
and Cloud
Computing
Learning Objectives (3 of 4)
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Data Centers and Cloud Computing
• Data Centers and Cloud Computing are types of IT
infrastructures or computing systems.
• A data center can also refer to the building or facility
that houses the servers and equipment.
• Today, companies may own and manage their own onpremises data centers or pay for the use of their
vendors’ data centers, such as in cloud computing, data
virtualization, and software-as-a-service arrangements
• When a data center goes down, so does business.
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Data Virtualization
• Data Virtualization
o Cisco’s single solution integrating computing, storage,
networking, virtualization, and management into a single
(unified) platform
o Virtualization gives greater IT flexibility and cutting costs:
• Instant access to data any time in any format
• Respond faster to changing data analytic needs
• Cut complexity and cost
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Data Virtualization Benefits
Compared to traditional data integration and replication methods
data virtualization accelerates time to value with:
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The Software–Defined Data Center (SDDC)
• An SDDC facilitates the integration of the various
infrastructures of the SDDC silos within organizations and
optimizes the use of resources, balances workloads, and
maximizes operational efficiency by dynamically distributing
workloads and provisioning networks.
• SDDC Goals: decrease costs and increase agility, policy
compliance and security by deploying, operating, managing
and maintaining applications.
• The base resources for the SDDC are computation, storage,
networking, and security.
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Figure 2.16 Corporate IT infrastructures can consist of an onpremises data center and off-premises cloud computing
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Cloud Computing
• What is “The Cloud”?
o A general term for infrastructure that uses the Internet and
private networks to access, share, and deliver computing
resources
o Scalable delivery as a service to end-users over a network
o A drawback of the cloud is control because a third party
manages it:
o Unless the company uses a private cloud within its network, it
shares computing and storage resources with other cloud users
in the vendor’s public cloud.
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Cloud Computing Types
• Private Cloud: delivers cloud computing services over
the Internet or a private internal network to only select
users instead of the general public.
• Public Cloud: is based on the standard cloud computing
model in which a service provider makes resources,
apps, or storage available to the general public over the
Internet either free or on a pay-per-usage model.
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Cloud Infrastructure
• The Value of the Cloud Infrastructure:
o Dynamic, not static
o Provides a way to make apps and computing power available
on demand because they are provided as a service
o Referred to as Software As A Service, or SaaS. (examples:
Google Apps and Salesforce.com)
o Helps companies become more agile and responsive while
significantly reducing IT costs and complexity
Large organizations are moving to Enterprise Clouds.
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Cloud Services


Services made available to users on demand via the
Internet from the servers of a cloud computing
provider instead of being accessed through an
organization’s on-premises servers.
The cloud computing model for on-demand delivery
of and access to various types of computing resources
also extends to the development of business apps.
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Anything-as-a-Service (XaaS) Models
(1 of 2)
1. Software as a Service (SaaS) — on-demand computing
and hosted services.
• Instead of buying and installing expensive packaged
enterprise applications, users can access software
applications over a network, using an Internet browser
2. Platform as a Service (PaaS) — a standard unified platform for
developing, testing, and deploying software over the Web
3. Infrastructure as a Service (IaaS) — a way of delivering servers,
storage, networks, workload balancers, and OSs as an ondemand service
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Anything-as-a-Service (XaaS) Models
(2 of 2)
4. Data as a Service (DaaS) – an information provision
and distribution model in which data files (including
text, images, sounds, and videos) are made available
to customers over a network by a service provider.
5. Technology solutions as a service (TSaaS) – combines
software, hardware, networks, and telecommunications to
provide specialized technology solutions that allow companies
to adopt new technologies and transform their business.
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Vendor Management and Cloud Service
Agreements
• Cloud Service Agreements
o A negotiated agreement between a company and service
provider that can be a legally binding contract or an informal
contract – also referred to as cloud service-level agreements
(SLAs)
o The goal is not building the best CSA terms, but getting the
terms that are most meaningful to the business needs.
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IS Concepts and
Classifications
IT
Infrastructure,
IT Architecture,
and Enterprise
Architecture
Virtualization
and Virtual
Machines
Data Centers
and Cloud
Computing
Learning Objectives (4 of 4)
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42
Virtualization and Virtual Machines
• Virtualization allows the sharing of a single physical
instance of an IT resource or app among multiple
customers and organizations.
• One of the most cost-effective, hardware-reducing, energysaving techniques used by cloud providers
• There are many types of virtualization, such as virtual
storage devices, virtual desktops, virtual OSs, and virtual
servers for network virtualization
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Figure 2.20 Virtual machines running on a simple computer hardware layer
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What Is a Virtual Machine?
• A virtual machine is a software-created computer.
Technically, a virtual machine (VM) is created by a
software layer, called the virtualization layer.
• That layer has its own Windows or other OS and apps,
such as Microsoft Office, as if it were an actual physical
computer.
• A VM behaves exactly like a physical computer and
contains its own virtual―that is, software-based―CPU,
RAM (random access memory), hard drive, and
network interface card (NIC).
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Virtualization Benefits
• Characteristics & Benefits
o Memory-intensive
• Huge amounts of RAM due to massive processing
requirements
o Energy-efficient
• Up to 95% reduction in energy use per server through less
physical hardware
o Scalability and load balancing
• Handles dynamic demand requests like during the Super
Bowl or World Series
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Author: Jeff Seaman
Part 1
Learning Objectives (1 of 4)
Doing Business in the OnDemand and Sharing Economies
Business Process Improvement
and Competition
IT and You
IT Innovation and Disruption
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Introduction
• Many forward-thinking managers and entrepreneurs are digitally
transforming their existing business models
• IT architectures guide the process of planning, acquiring,
building, modifying, and interfacing with deployed IT resources in
a single department within an organization.
• Legacy systems – older information systems
• Business leaders today need to know what steps to take to get
the most out of mobile, social, cloud, big data, analytics,
visualization technologies, artificial intelligence and the Internet
of Things (IoT) to move their business forward and enable new
on-demand and sharing business models.
4
Doing Business in the On-Demand and
Sharing Economies
• On-demand Economy is the economic activity created
by technology companies that fulfill consumer demand
through the immediate provisioning of products and
services.
• Sharing economy is an economic system in which goods
or services are shared between private individuals,
either free or for a fee, typically arranged through an
online company or organization.
5
Doing Business in the On-Demand and
Sharing Economies
• On-demand and shared services are propelled by
proliferation of:
Smartphone-connected consumers;
o Simple and secure purchase flows; and
o Location-based services
o
• Growth of app-driven companies like Airbnb, Uber,
GrubHub have disrupted markets.
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Doing
Business in
the OnDemand and
Sharing
Economies:
Airbnb,
Uber
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Doing Business in the On-Demand and
Sharing Economies: Terminology
• Business Model is a company’s core strategy for making
a profit.
• Digital Business Model is defined by how a business
makes money via digital technology.
• Customer Experience describes the cumulative impact
of multiple interactions over the course of a customer’s
contact with an organization.
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Seven
highly
disruptiv
e
business
models
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IT’s Role in the On-Demand and Sharing
Economies
• Companies are investing heavily in analytics,
cybersecurity, cloud, application software development
and maintenance, enterprise resource planning (ERP),
and customer relationship management (CRM).
• Data analytics is the process of examining data sets to
draw conclusions about the information they contain,
usually with the aid of specialized information systems.
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Business Objectives of IT (1 of 2)
1. Product Development—IT helps businesses respond quickly to
changing customer demands
2. Stakeholder Integration—companies use their investor relations
websites to communicate with shareholders, research analysts,
and others in the market
3. Process Improvement—An ERP systems replaces dozens of
legacy systems for finance, human resources, and other
functional areas, to increase efficiency and cost-effectiveness of
internal business processes
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Business Objectives of IT (2 of 2)
4. Cost Efficiencies—IT allows companies to reduce transaction and
implementation costs, such as costs of duplication and postage of
email vs snail mail.
5. Competitive Advantage—Companies can use agile development,
prototyping, and other systems methodologies to bring a product
to market cost effectively and quickly.
6. Globalization—companies can outsource most of their non-core
functions, such as HR and finance, to offshore companies and use
ICT to stay in contact with its global employees, customers and
suppliers 24/7
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Doing Business in the On-Demand and
Sharing Economies: I nfrastructure

Technology platform is the operating system and computer
hardware used as a base upon which other applications,
processes, or technologies are developed.

Technology stack is the multiple layers of hardware, software,
network connectivity, and data analytics capability that comprise
a technology platform.
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Doing Business in the On-Demand and
Sharing Economies: Questions (1 of 2)
1. Name four disruptive business models and describe what they
offer to their customers.
2. How is IT contributing to the success of the on-demand and
shared economies?
3. List the six IT business objectives
4. What are the key strategic and tactical questions that determine
an organization’s profitability and management performance?
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Doing Business in the On-Demand and
Sharing Economies: Questions (2 of 2)
5. What is a business model?
6. What is a digital business model?
7. Give two examples of how companies are transitioning to digital
business models.
8. What factors are driving the move to digital business models?
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Learning Objectives (2 of 4)
Doing Business
in the OnDemand and
Sharing
Economies
Business
Process
Improvement
and
Competition
IT and You
IT Innovation
and Disruption
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Business Process Improvement:
Terminology
• Competitive advantage is when an organization differentiates
itself by charging less and creating and delivering better quality
products or services than its competitors.
• Deliverables are tangible or intangible goods or services produced
in a project and intended to be delivered to a customer.
• Business Process is comprised of the activities that convert inputs
into outputs by doing work.
• Cross-functional business process involves two or more business
functions.
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Work that transforms input
& acts on data and
knowledge
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DELIVERABLES
Raw materials, data,
knowledge, expertise
ACTIVITIES
INPUTS
Three Components of a Business Process
Products, services, plans,
or actions
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Business Process Improvement:
Characteristics
• Business Process Characteristics
Formal Processes or Standard Operating Procedures (SOP):
documented and have well-established steps.
o Informal Processes: typically undocumented, undefined, or
are knowledge-intensive.
o Range from slow, rigid to fast-moving, adaptive.
o Can be rigid, resistant to change, or adaptive, responding to
change.
o Critical success factor (CSF) is an element that is necessary to
ensure the success of an organization or project, such as
access to adequate financial resources.
o
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Gaining a Competitive Advantage:
Components
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Learning Objectives (3 of 4)
Doing Business
in the OnDemand and
Sharing
Economies
Business
Process
Improvement
and
Competition
IT and You
IT Innovation
and Disruption
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IT Innovation and Disruption: Intro
SMAC Model
• Social-Mobile-Analytics-Cloud (SMAC) Model
Huge data centers accessible via the Internet form the core for the cloud by
providing 24/7 access to storage, apps, and services.
o Handheld and wearables and their users form the edge of the cloud.
o Social channels connect the core and edge.
o The SMAC integration creates the technical and services infrastructure
needed to digital business.
o
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IT Innovation and Disruption: SMAC
Influence
• Social-Mobile-Analytics-Cloud (SMAC)
Powerful social influences impact advertising and marketing.
o Consumer devices go digital and offer new services.
o eBay’s move to cloud technology improves sellers’ and buyers’
experiences
o
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IT Innovation and Disruption:
Technology Mega Trends (1 of 5)
Mega Trends are forces that shape or create the future of
business, the economy, and society.
• Connectivity
Need to connect across multiple channels and platforms
o Cloud computing is an Internet-based computing system
consisting of many computers and other devices where
computer infrastructure, access to applications, software,
processing power, and so on are shared.
o Digital resources no longer dependent on buying/owning that
resource.
o
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IT Innovation and Disruption:
Mega Trends (2 of 5)
• Big Data and Data Analytics
o
o
o
Big data is a process that is used when traditional data mining and handling techniques cannot uncover
the insights and meaning of the underlying data that are usually unstructured (text), time-sensitive, or
extremely large.
80-90% consists of Unstructured data, having no predictable format
Multiple channels and sources:

Machine-generated data from sensors and mobile devices

Social media content from texts, tweets, posts, blogs
29
IT Innovation and Disruption:
Mega Trends (3 of 5)
• Artificial Intelligence and Robotics
To improve their ability to meet evolving customer
expectations in a timely manner, digital innovators use
technology to automate, streamline, or eliminate their
processes.
o It is estimated that by 2022, artificial intelligence and machinelearning systems will handle most customer interactions.
o
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IT Innovation and Disruption:
Mega Trends (4 of 5)
• Digitization is the process of transforming any kind of
activity or information into a digital format that can be
collected, stored, searched, and analyzed electronically
and efficiently.
For example: Banks digitizing mortgage application/decision
process cut costs per new mortgage by 70%
o Dashboards is an easy-to-read, often single-page, real-time
user interface, showing a graphical presentation of the current
status and historical trends of an organization’s key
performance indicators to enable instantaneous and informed
decisions to be made.
o
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IT Innovation and Disruption:
Mega Trends (5 of 5)
• Machine-to-machine (M2M) Technology
Enables sensor-embedded products to share reliable real time
data via radio signals
o Internet of Things (IoT) refers to a set of capabilities enabled
when physical things are connected to the internet via sensors
o M2M and IoT are widely used to automate businesses ranging
from transportation to healthcare
o
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IT Innovation and Disruption:
COVID-19 Accelerates Digital
Transformation
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Learning Objectives (4 of 4)
Doing Business
in the OnDemand and
Sharing
Economies
Business
Process
Improvement
and
Competition
IT and You
IT Innovation
and Disruption
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IT and You: On-Demand ‘Gig’
Workers
U.S. On-Demand Workers (57 million)
• The three top reasons respondents gave for becoming
gig workers were:
Want to be an independent contractor, freelancer, temporary
worker or consultant (49%).
o Want to choose the number of hours they work (40%).
o Want to be able to work from any location (33%).
o
• On-demand workers typically receive their income from
three different sources:
o
On-demand work; Contracting and consulting; and Running a
business
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IT and You
• IT job growth in the United States is estimated at 12%
from 2018 to 2028, faster than the average for all other
occupations. This means about 546,200 new jobs.
• Global annual wages for IT professionals are at their
highest levels ever, averaging $89,732 (2019 Survey).
• By region, North American IT professionals earn
$109,985 on average—23% higher than the worldwide
average—followed by Europe, the Middle East, and
Africa at $70,445; the Asia-Pacific region at $65,738;
and Latin America at $41,465.
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IT and You
• Managing and Interpreting Big Data Are High Demand
Skills
Big data specialists manage and package big data collections,
analyze, and interpret trends and present their findings in
easy- to-understand ways to “C”-level executives
o Business intelligence (BI) analysts use tools and techniques to
go beyond the numbers of big data and act based on the
findings of the big data analyses
o
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IT and You
• IT Job Prospects
In 2020, less than 2% of all IT workers in the United States are
unemployed.
o Going forward, workers with specialized technical knowledge
and strong communications and business skills, as well as
those with an MBA with a concentration in an IT-related area,
will have the best prospects
o
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Chapter 3
Data Management, Data Warehouses, and
Data Governance
Learning Objectives (1 of 5)
Data
Management
Electronic
Document,
Record, and
Content
Management
Information
Management
Data
Warehouses
and Data
Marts
Data
Governance
and Master
Data
Management
(MDM)
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Data Management (1 of 2)
• Oversees the end-to-end lifecycle of data from creation
and initial storage to the time when it becomes
obsolete and is deleted.
• The goals of effective data management include:
1.
2.
3.
4.
5.
6.
Mitigating the risks and costs of complying with regulations.
Ensuring legal requirements are met.
Safeguarding data security.
Maintaining accuracy of data and availability.
Certifying consistency in data that come from or go to
multiple locations.
Ensuring that data conform to organizational best practices
for access, storage, backup, and disposal.
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Data Management (2 of 2)
• Benefits of data management include:
1.
2.
3.
4.
5.
6.
greater compliance
higher security
less legal liability
improved sales and marketing strategies
better product classification
improved data governance to reduce risk.
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Data Management: Database
Technologies
• Database: A collection of data sets or records stored in
a systematic way
• Database management system: (DBMS) Software that integrates
with data collection systems to store data in an organized way
and provide facilities for accessing and managing data.
• Data warehouse: Large data set that integrates data from
multiple databases and data silos across the organization, and
organizes them for complex analysis, knowledge discovery, and
to support decision-making.
• Data mart: A small-scale data warehouse that supports a single
function or one department.
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Data Management: Databases
• Transaction: a single logical unit of work that accesses
and possibly modifies the contents of a database.
• Centralized database: stores all data as a unified body
in a single central computer such as a mainframe or
server in one physical location.
• Distributed database: stores portions of the database
on multiple computers controlled by a database
management system (DBMS) within a network in a
client-server configuration.
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Data Management: Centralized
database
Benefits
1. Better control of data
quality
2. Ease of use
3. Better IT security
4. Better data integrity
Disadvantages
1. Transmission delay
2. Security
3. Reliability
4. Scalability
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Data Management: Distributed
databases
Advantages
1. Security
2. Reliability
3. Speed
4. Scalability
Disadvantages
1. Availability
2. Expense
3. Security
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Database Management System (DBMS)
• Online transaction processing (OLTP): a database
design that breaks down complex information into
simpler data tables to strike a balance between
transaction processing efficiency and query efficiency.
• Online analytics processing (OLAP): the analysis of
complex data from a data warehouse.
Copyright ©2021 John Wiley & Sons, Inc.
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Database Management: Elements of a DBMS
• Four important elements:
1. data structure
2. data modeling language
3. data query language, and
4. transaction mechanisms.
Copyright ©2021 John Wiley & Sons, Inc.
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Elements of a DBMS: Data structure
• A specialized format for organizing and storing
data. General data structures include, file, record,
table, tree, and so on.
Copyright ©2021 John Wiley & Sons, Inc.
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Elements of a DBMS:
Data modeling
language
• Approaches to the modeling
language of the DBMS include
hierarchical, network,
relational, and object-oriented.
Copyright ©2021 John Wiley & Sons, Inc.
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Data modeling
language: Network
A data model that allows
multiple records to be
linked to the same
parent.
Copyright ©2021 John Wiley & Sons, Inc.
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Data modeling
language:
Relational
• An approach to managing
data using a structure and
language that involves the
use of data tables to collect
groups of elements into
relations.
Copyright ©2021 John Wiley & Sons, Inc.
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Data modeling
language: ObjectOriented (OO)
• A data model that
supports the modelling and
creation of data entities as
objects that contain both
data and the relationships of
those data.
Copyright ©2021 John Wiley & Sons, Inc.
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Data modeling
language:
Blockchain
• A distributed ledger
represented by a sequential
chain of data blocks that
records transactions,
establishes identity of the
user, and establishes
contracts.
Copyright ©2021 John Wiley & Sons, Inc.
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Data modeling language: Blockchain





Blockchains are also designed to be secure and build trust.
The blocks in a blockchain are chained together using
cryptographically created keys (hash).
Hash: a function that takes an input value and outputs a unique
fixed-size hexadecimal number that is the cryptographically
created key for the data.
Proof-of-work and peer-to-peer network are two other
mechanisms that are used to boost the security of the
blockchain.
In all industry sectors, the level of trust and security that
currently only blockchain can offer is critical to a secure supply
chain.
Copyright ©2021 John Wiley & Sons, Inc.
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Elements of a DBMS:
Data Query Language
• Query is an ad hoc
(unplanned) user request for
specific data.
• Structure Query Language (SQL) is the most widely-used mainstream
declarative language that works with any database to simplify data access by
requiring that users only declare what data they want rather than tell the
DBMS how to get it.
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• NoSQL is a non-relational database
query language.
Data
Query
Language:
Not Only
SQL
(NoSQL)
• The advantages of NoSQL include:
• higher performance
• easy distribution of data on different
nodes, which enables scalability and
fault tolerance
• greater flexibility
• simpler administration
• NewSQL is the latest type of
scalable database that supports a
SQL interface. It combines the
reliability of SQL and the speed and
performance of NoSQL to provide
better functionality and services and
provide database administrators
with ACID performance guarantees.
Copyright ©2021 John Wiley & Sons, Inc.
22
DBMS Vendor Rankings

The top five enterprise database management
systems of 2019 are:
1. Oracle’s Database 18c,
2. Microsoft SQL Server 2019,
3. IBM DB2,
4. SAP Sybase ASE, and
5. PostgreSQL
Copyright ©2021 John Wiley & Sons, Inc.
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Data Management : Questions
1.
2.
3.
4.
Describe the purpose and benefits of data management.
Define a database and a database management system (DBMS).
What are the four elements of a DBMS?
Explain what an online transaction-processing (OLAP) system
does, and which database technology is most appropriate for its
use.
5. Describe the functions of a DBMS.
6. What is a relational database management system?
7. What are the main elements of a block in a blockchain?
8. What are the three mechanisms that help keep a blockchain
secure?
Copyright ©2021 John Wiley & Sons, Inc.
24
Learning Objectives (2 of 5)
Data
Management
Electronic
Document,
Record, and
Content
Management
Information
Management
Data
Warehouses
and Data
Marts
Data
Governance
and Master
Data
Management
(MDM)
Copyright ©2021 John Wiley & Sons, Inc.
25
Data Warehouses and Data Marts
• Data warehouse is a central depository of integrated
data from one or more disparate sources.
• Data mart is a small-scale data warehouse that
supports a single function or one department.
Copyright ©2021 John Wiley & Sons, Inc.
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Moving Data from a Database to a Data
Warehouse or a Data Mart
• Data are moved in three main steps:
1. Extracted from designated databases.
2. Transformed by standardizing formats, cleaning the
data, and integrating them.
3. Loaded into a data warehouse.
Copyright ©2021 John Wiley & Sons, Inc.
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Copyright ©2021 John Wiley & Son, Inc.
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Building and Using a Data Warehouse
Copyright ©2021 John Wiley & Son, Inc.
29
Real-Time Support from an Active Data
Warehouse

Active data warehouse (ADW): the technical ability to
capture transactions when they change and integrate
them into the warehouse along with maintaining bath
or scheduled cycle refreshes.
• Companies with an ADW are able to:
• Interact with a customer to provide superior
customer service.
• Respond to business events in near real time.
• Share up-to-date status data among merchants,
vendors, customers, and associates.
Copyright ©2021 John Wiley & Sons, Inc.
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Data Warehousing Supports Action as
Well as Decisions


Data warehouses are infrastructure investments that
companies in a variety of industries make to support
ongoing and future operations, including: Marketing,
Pricing and contracts, Forecasting, Sales, and Financial
Enterprise data warehouses (EDWs) are data
warehouses that integrate data from many different
databases across an entire enterprise.
Copyright ©2021 John Wiley & Sons, Inc.
31
Data Lakes
• A single store of
structured, semi-structured,
and unstructured enterprise
data stored in its natural
format.
Copyright ©2021 John Wiley & Sons, Inc.
32
Data Warehouses and Data Marts: Questions
1. What are the differences between databases and data
warehouses?
2. What are the differences between data warehouses and data
marts?
3. Explain ETL.
4. Explain CDC.
5. What is an advantage of an enterprise data warehouse (EDW)?
6. Why might a company invest in a data mart instead of a data
warehouse?
7. What levels of an organization benefit most from a data
warehouse?
8. How is a data lake different from a data warehouse?
Copyright ©2021 John Wiley & Sons, Inc.
33
Learning Objectives (3 of 5)
Data
Management
Electronic
Document,
Record, and
Content
Management
Information
Management
Data
Warehouses
and Data
Marts
Data
Governance
and Master
Data
Management
(MDM)
Copyright ©2021 John Wiley & Sons, Inc.
34
Data Governance and Master Data
Management (MDM)
• Data governance is the overall management of the
availability, usability, integrity, and security of data used
in an enterprise.
• Three industries that rely heavily on data governance:
• Food industry
• Financial services industry
• Health-care industry
Copyright ©2021 John Wiley & Sons, Inc.
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Copyright ©2021 John Wiley & Sons, Inc.
36
Master Data and Master Data
Management (MDM)
• Master data: the term used to describe businesscritical information on customers, products and
services, vendors, locations, employees, and other
things needed for operations and business transactions
• Master data management (MDM) integrates data from
various sources or enterprise applications to create a
more complete (unified) view of a customer, product,
or other entity.
Copyright ©2021 John Wiley & Sons, Inc.
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Copyright ©2021 John Wiley & Sons, Inc.
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Master Reference File and Data Entities
• Data entity is anything real or abstract about which a
company wants to collect and store data.
• Master file is a collection of records describing one of
the main entities in a database, such as customers,
products, employees, and vendor. It is usually
periodically updated.
• Customer-centric is an approach to doing business that
focuses on providing a positive customer experience at
and after the point of sale to drive profit and gain
competitive advantage.
Copyright ©2021 John Wiley & Sons, Inc.
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Benefits of Data Governance and
Master Data Management
1. Improved regulatory compliance
2. More efficient decision-making
3. Improved data understanding
4. Increased revenue
Copyright ©2021 John Wiley & Sons, Inc.
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Data Governance and Master Data
Management (MDM): Questions
1. Explain why it is important to develop an effective data
governance program?
2. Explain the purposes of master data management.
3. Why has interest in data governance and MDM increased?
4. What are two ways that data is used in business?
5. What are three benefits of data governance.
Copyright ©2021 John Wiley & Sons, Inc.
41
Learning Objectives (4 of 5)
Data
Management
Electronic
Document,
Record, and
Content
Management
Information
Management
Data
Warehouses
and Data
Marts
Data
Governance
and Master
Data
Management
(MDM)
Copyright ©2021 John Wiley & Sons, Inc.
42
Information Management
• Information management is the process of collecting,
storing, managing, and maintaining data that is
accurate, timely, reliable, valid, available, unique, and
relevant to an organization
Copyright ©2021 John Wiley & Sons, Inc.
43
Data Life Cycle and Data Principles (1 of 2)
Copyright ©2021 John Wiley & Sons, Inc.
44
Data Life Cycle and Data Principles (2 of 2)
• Three general data principles relate to the data life
cycle perspective and help guide IT investment
decisions. These are:
1. Principle of diminishing data value
2. Principle of 90/90 data use
3. Principle of data in context
Copyright ©2021 John Wiley & Sons, Inc.
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Breaking
Down Data
Silos
• Data silo are standalone data stores.
Their data are not
accessible by other
ISs that need it or
outside that
department.
Copyright ©2021 John Wiley & Sons, Inc.
46
Culture Must Change
• Moving from silos to collaboration requires a culture
change:
1. Publicly acknowledge shared goals
2. Embrace the “why”
3. Culture comes from the top
Copyright ©2021 John Wiley & Sons, Inc.
47
Garbage In, Garbage Out
• Dirty data are data of such poor quality that they
cannot be trusted or relied upon for decisions
• Inaccurate Data
• Missing Data
• Poorly Designed Interfaces
• Nonstandardized Data Formats
• Outdated Data
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Copyright ©2021 John Wiley & Sons, Inc.
49
The Cost of Dirty Data
• Lost business
• Time spent preventing errors
• Time spent correcting errors
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50
Information Management Benefits
1. Improved decision quality
2. Improved accuracy and reliability of management
predictions
3. Lower time and cost
4. Better data quality
Copyright ©2021 John Wiley & Sons, Inc.
51
Learning Objectives (4 of 5)
Data
Management
Electronic
Document,
Record, and
Content
Management
Information
Management
Data
Warehouses
and Data
Marts
Data
Governance
and Master
Data
Management
(MDM)
Copyright ©2021 John Wiley & Sons, Inc.
52
Electronic Document, Record,
and Content Management
• Electronic content is a collection of documents,
records, and unstructured data available as a broad
range of digital assets, such as audio, video, flash,
multimedia files, and so on.
• Electronic document is any paper, electronic form, file,
email, fax, contract, lease, and so on actively being
worked on.
• Electronic record is any document that has been made
final and is no longer meant to be altered.
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54
Electronic Document Management, EDMS,
and Electronic Records Management
• Electronic document management is the electronic
storage, maintenance, and tracking of electronic
documents and electronic images of paper-based
information.
• Electronic document management system is a
software system for creating, organizing, storing, and
retrieving different kinds of electronic documents.
• Electronic record management establishes policies and
standards for maintaining diverse types of records.
Copyright ©2021 John Wiley & Sons, Inc.
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Electronic Records Management Systems
• ERMS is the technology tool used to electronically manage the
creation and maintenance of records within classification
schemes, apply retention and disposal schedules, and control
access and use.
• ERMS can help a business by:
• Enabling the company to access and use the content
contained in documents.
• Cutting labor costs by automating business processes.
• Reducing the time and effort required to locate information
the business needs to support decision-making.
• Improving the security of content, thereby reducing the risk of
intellectual property theft.
• Minimizing the costs associated with printing, storing, and
searching for content.
Copyright ©2021 John Wiley & Sons, Inc.
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Enterprise Content Management and
ECMS
• Enterprise content management is the capture, storage,
retrieval, and management of a diverse set of digital
assets including documents, records, emails, electronic
communications, images, video, flash, audio, and
multimedia.
• Enterprise content management system (ECMS)
captures, preserves, and manages structured and
unstructured a wide variety of digital assets and
secures them digitally in compliance with policies.
Copyright ©2021 John Wiley & Sons, Inc.
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Choosing an EDMS, ERMS, or ECMS (1 of 2)
• When choosing an EDMS, ERMS, or ECMS it is important to
match the strategic needs of the company with the capabilities
of the system
• Critical differences between an EDMS and an ERMS:
1.
2.
EDMS users need to check in and check out stored
documents quickly and easily and unlock them for future
revision, while maintaining version tracking and histories of
access, whereas ERMS users require that records be kept
in their original format for retrieval for compliance or legal
reasons
Software security is essential in an ERMS, but only
desirable in a EDMS.
Copyright ©2021 John Wiley & Sons, Inc.
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Choosing an EDMS, ERMS, or ECMS (2 of 2)
• An ECMS has a broader mission. It differs from EDMS and ERMS
in that:
1. It is designed to facilitate record lifecycle management,
information governance, and collaboration.
2. An ECMS also provides a single source of trusted
information. It also provides version control and
synchronization, along with intuitive search and
discovery functions.
3. An ECMS also can integrate with other applications to
deliver viewable content across multiple platforms,
along with security and optimized business processes
in its content storage and retrieval systems
Copyright ©2021 John Wiley & Sons, Inc.
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