Knowledge Management

1.    Define knowledge management and describe its purposes.
Knowledge management (KM) is the systematic and active management of ideas, information, and knowledge residing in an organization’s employees.
    Its purposes include effective and efficient problem solving, dynamic learning, strategic planning, and decision making. KM initiatives focus on identifying knowledge, explicating it in such a way that it can be shared in a formal manner, and leveraging its value through reuse.

Collaborative Computer-Supported Technologies and Group Support Systems

1.    Define groupwork.
Groupwork is “work done by two or more people together.”

2.    List five characteristics of groupwork.
The text gives the characteristics listed below. A correct answer can consist of any five:
•    A group performs a task (sometimes decision making, sometimes not).
•    Group members may be located in different places.
•    Group members may work at different times.
•    Group members may work for the same organization or for different organizations.
•    A group can be permanent or temporary.
•    A group can be at one managerial level or can span several levels.
•    There can be synergy (leading to process and task gains) or conflict in groupwork.
•    There can be gains and/or losses in productivity from groupwork.
•    The task may have to be accomplished very quickly.
•    It may be impossible or too expensive for all the team members to meet in one place, especially when the group is called for emergency purposes.
•    Some of the needed data, information, or knowledge may be located in many sources, some of which may be external to the organization.
•    The expertise of non-team members may be needed.
•    Groups perform many tasks; however, groups of managers and analysts frequently concentrate on decision making.
•    The decisions made by a group are easier to implement if supported by all (or at least most) group members.

Data Mining for Business Intelligence

1.                  Define data mining. Why are there many different names and definitions for data mining?

Data mining is the process through which previously unknown patterns in data were discovered. Another definition would be “a process that uses statistical, mathematical, artificial intelligence, and machine learning techniques to extract and identify useful information and subsequent knowledge from large databases.” This includes most types of automated data analysis. A third definition: Data mining is the process of finding mathematical patterns from (usually) large sets of data; these can be rules, affinities, correlations, trends, or prediction models.

Data mining has many definitions because it’s been stretched beyond those limits by some software vendors to include most forms of data analysis in order to increase sales using the popularity of data mining.

Q & A Review on Decision Making, Modeling, & Support

1.     Q: What are some of the key questions to be asked in supporting decision making through DSS?
             A:
•    What are the root issues underlying the decision situation?  Do we understand the problem sufficiently to support it? 
•    How structured is the decision? Is it unstructured, semi-structured, or structured?
•    Does the decision involve judgment? To what extent?
•    What data is needed to solve the problem?
•    Can an existing tool be leveraged or reused?
•    Is a tool needed?
•    What is the implementation plan?

Q & A Review on DSS & BI

1.    Q: List the components of and explain the Business Pressures–Responses–Support model.
A: The components of the pressure-response-support model are business pressures, companies’ responses to these pressures, and computerized support. The model suggests that responses are made to counter the pressures or to take advantage of opportunities, support facilitates monitoring the environment (e.g., for opportunities) and enhances the quality of the responses.