Many organizations now view information as one of their most valuable assets, and data mining software allows a company to make full use of these information assets. Data mining software analyzes relationships and patterns in stored transaction data based on open-ended user queries. Several types of analytical software are available: statistical, machine learning and neural networks, decision trees, naive-Bayes, K-nearest neighbor, rule induction, clustering, rules based, linear and logistical regression time sequence, and so forth (Wang, 2005). There is never enough time to think of all the important questions; that is why the computer should do this itself. It can provide the winning edge in business by exploring the database and it brings back invaluable information.
Key Terms in this Chapter
Modifiability: The degree of augment ability and the ability to change and expand over time.
GUI (Graphical User Interface): The screen interface with a computer’s operating software where graphical components such as icons are used to represent computer files and programs. The usual range of graphical components in such an interface normally includes windows, icons, menus, and pointers, and as a result is sometimes referred to as WIMP interfaces.
Reliability: The probability of performing a specified function without failure under given conditions for a specified period of time.
Human Engineering: The extent to which a software product fulfills its purpose without wasting users’ time and energy or degrading their morale.
Portability: The ability of a program to be run in various environments, operating systems, and so forth.
Understandability: The degree to which the purpose of the system or component is clear to the evaluator.
Efficiency: Measure of actual output over effective capacity or the ratio of output to input.
Testability: The degree to which a system or component facilitates the establishment of test criteria and the performance of tests to determine whether those criteria have been met.