Chapter 11: Data, Knowledge, and Decision Support

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Transcript Chapter 11: Data, Knowledge, and Decision Support

Introduction to Information Technology
2nd Edition
Turban, Rainer & Potter
© 2003 John Wiley & Sons, Inc.
Chapter 11:
Data, Knowledge, and Decision Support
Prepared by:
Roberta M. Roth, Ph.D.
University of Northern Iowa
Introduction to Information Technology, 2nd Edition
Turban, Rainer & Potter
© 2003 John Wiley & Sons, Inc.
11-1
Chapter Preview
 In this chapter, we will study:
 The decision making process and how IT can support it
 Various types of decision support, including DSS, EIS,
and GDSS
 Methods of analyzing and mining stored data
 Ways of presenting information through data
visualization techniques
 Knowledge management and how it can benefit an
organization
Introduction to Information Technology, 2nd Edition
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© 2003 John Wiley & Sons, Inc.
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Why Do Managers Need IT Support?
 Volume of available information is staggering
 Manually processing information quickly is
increasingly difficult
 Computerized modeling helps manage complexity
examine numerous alternatives very quickly
provide a systematic risk analysis
Introduction to Information Technology, 2nd Edition
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© 2003 John Wiley & Sons, Inc.
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Where do we get the data we need?
 Data Sources
Internal Data
Personal Data
External Data
 Data Collection Methods
Manually
By instruments and sensors
Scanning or electronic transfer
Introduction to Information Technology, 2nd Edition
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© 2003 John Wiley & Sons, Inc.
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What is ‘good’ data?
 Data Quality
quality determines the data’s usefulness as
well as the quality of the decisions based on
these data
an extremely important issue
characteristics of high quality data: accurate,
secure, relevant, timely, complete, and
consistent
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© 2003 John Wiley & Sons, Inc.
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Data Storage and Management
 Data Storage
 Databases or in data warehouse and data marts
 Data Management difficulties
 Data volume exponentially increases with time
 Many methods and devices used to collect data
 Raw data stored many places and ways
 only small portions of data are relevant for specific
situations
 More and more external data
 Different legal requirements relating to data
 Difficulty selecting data management tools
 Data security, quality, and integrity are essential
Introduction to Information Technology, 2nd Edition
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© 2003 John Wiley & Sons, Inc.
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Document Management Systems
 Much data is contained in documents
 DMS manage electronic documents
 Provide control over and access to
documents within organization
 Imaging systems, workflow software, and
databases are utilized to efficiently
capture and control documents
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Business Intelligence
 Ultimate goal of collecting data is to
provide a foundation for business
intelligence
 All data needed for sound decisions
 Data is drawn from data warehouses or data
marts
 Data analysis tools are applied
 Decision makers’ judgment is augmented with
facts, analysis, and forecasts
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© 2003 John Wiley & Sons, Inc.
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Decision Making Process
REALITY


SUCCESS
Examination
Intelligence Phase
Validation of
the Model
Design Phase
Verification, Testing
of Proposed Solution
Choice Phase
Implementation
of Solution
FAILURE
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© 2003 John Wiley & Sons, Inc.

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Decision Making Process (continued)
 Decision Support Systems supply
computerized support for the decision
making process
 End-users actively work with the data
warehouse
 End-users apply models to represent,
understand, and simplify the decision
situation
Introduction to Information Technology, 2nd Edition
Turban, Rainer & Potter
© 2003 John Wiley & Sons, Inc.
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Introduction to Information Technology, 2nd Edition
Turban, Rainer & Potter
© 2003 John Wiley & Sons, Inc.
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Introduction to Information Technology, 2nd Edition
Turban, Rainer & Potter
© 2003 John Wiley & Sons, Inc.
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Introduction to Information Technology, 2nd Edition
Turban, Rainer & Potter
© 2003 John Wiley & Sons, Inc.
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What do we mean by ‘model’?
 Model - simplified representation of reality
Iconic (scale) models
• physical replica of a system
Analog models
• Behaves like real system; does not look like it
Mathematical (quantitative) model
• models complex relationships and conducts
experimentations with them
Mental models
• how a person thinks about a situation
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© 2003 John Wiley & Sons, Inc.
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Thinking about decisions…
 A Framework for Computerized Decision Support
 Problem Structure
• decision making processes fall along a continuum that ranges
from highly structured to highly unstructured decisions
 Nature of Decisions
• strategic planning - the long-range goals and policies for
resource allocation
• management control - the acquisition and efficient utilization
of resources in the accomplishment of organizational goals
• operational control - the efficient and effective execution of
specific tasks
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Thinking about decisions…
 Structured decisions have long been
supported by computers
 Classes of structured decisions have been
addressed mathematically with
Management Science models
Define the problem
Classify the problem into a standard category
Construct a standard mathematical model
Find potential solutions
Choose and recommend a specific solution
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Decision Support Systems
 Needed when decision is not structured
 Characteristics and Capabilities
 Support decision makers at all managerial levels
 Support several interdependent and/or sequential
decisions
 Support all phases of decision making and a variety of
decision-making processes and styles
 Can be adapted over time to deal with changing
conditions
 Easy to construct
 Utilizes models and links to data- and knowledge bases
 Execute sensitivity analysis
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DSS (continued)
 Sensitivity Analysis
the study of the effect that changes in one or
more parts of a model have on other parts of
the model
 What-if Analysis
checks the impact of a change in the
assumptions or other input data on the
proposed solution
 Goal-seeking Analysis
find the value of the inputs necessary to
achieve a desired level of output
Introduction to Information Technology, 2nd Edition
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© 2003 John Wiley & Sons, Inc.
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DSS (continued)
 Components and Structure of DSS
 Data Management
• Includes the database(s) containing relevant data for the
decision situation
 User Interface
• Enables the users to communicate with and command the
DSS
 Model Management
• Includes software with financial, statistical, management
science, or other quantitative models
 Knowledge Management
• Provides knowledge for solution of the problem; supports any
of the other subsystems or act as an independent component
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© 2003 John Wiley & Sons, Inc.
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Enterprise Decision Support
 Executive Information Systems
Meet information needs of executives
• Need to monitor and identify problematic trends
• Need external as well as internal information
Rapid access to data needed by executives
Very easy user interface
Highly graphical
Often connected with online information
services (e.g., Dow Jones News Retrieval)
Introduction to Information Technology, 2nd Edition
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© 2003 John Wiley & Sons, Inc.
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Enterprise Decision Support
 Executive Information Systems (continued)
 Capabilities of EIS
• Drill down
• Critical success factors and key performance
indicators
• Status access
• Trend analysis
• Ad hoc analysis
• Exception reporting
• Intelligent EIS
• Integration with DSS; web accessibility
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© 2003 John Wiley & Sons, Inc.
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Enterprise Decision Support
 Group Decision Support Systems
 Facilitate solution of semistructured and unstructured
decisions by a group of decision makers
 Help the group be productive by mitigating some
negative group behaviors
 Support the group’s process by encouraging idea
generation, improving communication, and applying
analytical tools as needed to the problem
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© 2003 John Wiley & Sons, Inc.
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Enterprise Decision Support
 GDSS Implementations
 Face-to-face meetings – special ‘decision room’
created with linked computers and GDSS software; use
is facilitated by trained leader
 Corporate ‘war room’ – information displayed
graphically and analyses conducted for all to see
 Support for virtual teams – collaborative team tools
for geographically dispersed teams; support discussion,
calendars, polling, etc.
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© 2003 John Wiley & Sons, Inc.
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What can we do with the stored data?
 Analytical Processing - the activity of
analyzing accumulated data
 Online analytical processing (OLAP)
An end-user activity
Involve large data sets with complex
relationships
Use Decision Support Systems models
Is retrospective
Introduction to Information Technology, 2nd Edition
Turban, Rainer & Potter
© 2003 John Wiley & Sons, Inc.
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Online Analytical Processing (OLAP)
 Analysis by end users from their desktop, online,
using tools like spreadsheets
 Analyze the relationships between many types of
business elements
 Involve aggregated data
 Compare aggregated data over hierarchical time
periods (monthly, quarterly, annually)
 Present data in different perspectives
 Involve complex calculations between data
elements
 Respond quickly to users requests
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Turban, Rainer & Potter
© 2003 John Wiley & Sons, Inc.
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Data Visualization
 Analyzed data can be even more useful if
presented using Data Visualization techniques
 Visual Interactive Modeling – graphic display of decision
consequences
 Visual Interactive Simulation – simulation model is
animated and can be viewed and modified by decision
maker
 Geographic Information Systems – display data related
to geographic location using digitized maps
Introduction to Information Technology, 2nd Edition
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© 2003 John Wiley & Sons, Inc.
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Chapter Summary
 High quality data can be analysed to improve





decision making
DSSs help decision makers with semi- or
unstructured decisions
Executives can use EISs tailored to their
information needs
GDSSs support group decision activities
Data analysis and data mining help in
understanding and discovery of new insight
Knowledge is also an organizational resource
that can be stored and managed
Introduction to Information Technology, 2nd Edition
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© 2003 John Wiley & Sons, Inc.
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Introduction to Information Technology, 2nd Edition
Turban, Rainer & Potter
© 2003 John Wiley & Sons, Inc.
11-29