chapter 9 : Streaming Business Operation

Decision Making

Reasons for the growth of decision -making information systems.

• People must make decisions quickly.
• People need to analyze large amounts of information.
• People must protect the corporate asset of organizational information.

• -model-a simplified representation or abstraction of reality.

Transaction processing systems-the basic business system that serves the operational level in an organization.

1. 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.
2. Online analytical processing (OLAP)- the manipulation of information to create business intelligence in support of strategic decision making.
3. Desicion support system (DSS)-models information to support managers and business professionals during the decision -making process.

Three quantitative models used by DSSs include:

1. Sensitivity analysis-the study of the impact that changes in one 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 (EIS)-a specialized DSS that supports senior level executives within the organization.

• Consolidation-involves the aggregation of information and features simple rolls-ups to complex groupings of interrelated information.
• Drill-down-enables users to get details, and details of details, of information.
• Slice-and-dice-looks at information from different perspectives.

• -Digital dashboard-integrates information from multiple components and presents it in an unified display.
• -Intelligent system-various commercial applications of artificial intelligence.
• -Artificial intelligence-simulates human intelligence such as the ability to reason and learn.

4 most common categories:

1. Expert system-computerized advisory program that imitate the reasoning processes of experts in solving difficult problems.
2. Neutral network-atempts to emulate the way the human brain works.
3. Genetic algorithm- an artifical 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.
 

Common data mining analysis capabilities-cluster analysis,association detection, statistical analysis.

• CLUSTER ANALYSIS-a technique used to divide an information set into mutually exclusive groups such that the members of each group are as close together as possible to one another and the different groups are as far apart as possible.

• ASSOCIATION DETECTION-reveals the degree to which variables are related and the nature and frequency of these relationships in the information.

• -Market basket analysis-analyzes such as items as web sites and checkout scanner information to detect customers'buying behavior and predict future behavior by identifying affinities among customers choices of products and services.

• STATISTICAL ANALYSIS-performs such functions as information correlations,   distributions, caculations, and variance analysis.

• - forescast-predictions made on the basis of time-series information.
• -time-series information-time-stamped information collected at a particular frequency.