DECISION SUPPORT SYSTEMS
-Decision support systems (DSS) – models information to support managers and business professionals during the decision-making process
-Three quantitative models used by DSSs include :
1. Sensitively 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 output
EXECUTIVE INFORMATION SYSTEMS
-Executive information system (EIS) – a specialized DSS that supports senior level executives within the organization
-most EISs offering the following capabilities :
1.consolodation– involves the aggregation of intelligent system that mimics the evolutionary, survival-of-the-fittest process to generate increasingly better solutions to a problem
2.drill-down – enables, users to get details and details of details, of information
3.slice-and-dice – looks at information from different perspectives
ARTIFICIAL INTELLIGENCE
-INTELLIGENT SYSTEM – various commercial applications of artificial intelligence
-ARTIFICIAL INTELLIGENCE (AI) – Simulates human intelligence such as the ability to reason and learn
-advantages: can check info on competitor
-the ultimate goal of AI is the ability to build a system that can mimic human intelligence
-Four most common categories of AI include :
1. expert system – computerized advisory programs that imitate the reasoning processes of expert in solving difficult problems
2. neural network – attempts to emulate the way the human brain works
-fuzzy logic – a mathematical method of handling imprecise or subjective information
3. genetic algorithm – an AI system that mimics the evolutionary, survival-if-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
-data-mining software includes many forms of AI such as neural networks and expert system
-common forms of data-mining analysis capabilities include:
1. cluster analysis
2. association detection
3. statistical analysis
CLUSTER ANALYSIS
-CLUSTER ANALYSIS – To divide an information set into mutually exclusive groups such that the members of each group are as possible to one another and the different groups are as far apart as possible
-CRM systems depend on cluster analysis to segment customer information and identify behavioral traits
ASSOCIATION DETECTION
-Association detection reveals the degree to which variables are related and the nature and frequency of these relationships in the information
-Market basket analysis such items as Web sites and checkout scanner information to detect customers’ buying behavior and predict future behaviour by identifying affinities among customers’ choices of products and services
STATISTICAL ANALYSIS performs such functions as information correlations, distributions, calculations and variance analysis
- forecast– predictions made on the basis of time-series information
- time-series information – time-stamped information collected at a particular frequency
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