Decision Making
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Reasons for Growth of Decision Making
Information System
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People need to analyze large amounts of
information – Improvements in technology itself, innovations in communication,
and globalization have resulted in a dramatic increase in the alternatives and
dimensions people need to consider when making a decision or appraising an
opportunity
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People must make decisions quickly – Time is of
the essence and people simply do not have time to sift through all the
information manually
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People must apply sophisticated analysis
techniques, such as modeling and forecasting, to make good decisions – Information systems
substantially reduce the time required to perform these sophisticated analysis
techniques
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People must protect the corporate asset of
organizational information – Information systems offer the security required to
ensure organizational information remains safe.
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Model – A simplified representation or
abstraction of reality
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IT systems in an enterprise
Transaction Processing System
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Moving up through the organizational pyramid
users move from requiring transactional information to analytical information
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Transaction processing system – the basic
business system that serves the operational level (analysis) in an organization
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Online transaction processing (OLTP) – the
capturing of transaction and event information using technology to (1) process
the information according to defined business rules, (2) store the information,
(3) update existing information to reflect the new information
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Online analytical processing (OLAP) – the
manipulation of information to create business intelligence in support of
strategic decision making
Decision support systems
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Decision support system (DSS) – models
information to support managers and business professionals during the
decision-making process
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Three quantitative models used by DSSs include;
1.
Sensitivity analysis – the study of the impact
that changes in one (or more) parts of the model have on other parts of the
model
2.
What-if analysis – checks the impact of a change
in an assumption on the proposed solution
3.
Goal-seeking analysis – finds the inputs
necessary to achieve a goal such as a desired level of outputs
What-if analysis
Goal-seeking analysis
Executive information system
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Executive information system (EIS) – A
specialized DSS that supports senior level executives within the organization
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Most EISs offering the following capabilities;
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Consolidation – involves the aggregation of
information and features simple roll-ups to complex groupings of interrelated
information
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Drill-down – enables users to get details, and
details of information
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Slice-and-dice – looks at information from
different perspectives
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Interaction between a TPS and an EIS
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Interaction between a TPS and a DSS
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Digital dashboard – integrates information from
multiple components and presents it in a united display
Artificial intelligence (AI)
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The ultimate goal of AI is the ability to build
a system that can mimic human intelligence
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Intelligent system – various commercial
applications of artificial intelligence
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Artificial intelligence (AI) – simulates human
intelligence such as the ability to reason and learn
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Four most common categories of AI include;
1.
Expert system – computerized advisory programs
that imitate the reasoning processes of experts in solving difficult problems
2.
Neural network – attempts to emulate the way the
human brain works
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Fuzzy logic – a mathematical method of handling
imprecise or subjective information
3.
Genetic algorithm – an artificial intelligent
system that mimics the evolutionary, survival-of-the-fittest process to
generate increasingly better solutions to a problem
4.
Intelligent agent – special-purposed
knowledge-based information system that accomplishes specific tasks on behalf
of its users
Data Mining
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Data-mining software includes many forms of AI
such as neutral networks and expert systems
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