Decision Making
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Reasons for Growth of Decision
Making Information System
- 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
- People must make decisions quickly – Time is of the
essence and people simply do not have time to sift through all the information
manually
- 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
- 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;
- Consolidation – involves the aggregation of
information and features simple roll-ups to complex groupings of interrelated
information
- Drill-down – enables users to get details, and details
of information
- 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
o 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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