1. Decision Support Systems DSS.

2. Prostration Group 3 2575 2729 2397 2742 2659 2488

3.  Component DSS  Types DSS  Characteristic DSS  decision support in business  business and decision support  Management information system  Online Analytical processing  Decision support systems  Using Decision support systems  Executive information system  Knowledge management system

4.  Database  The model  Behavioral model  Management science model Component of decision support system

5. Characteristics and capabilities of (DSS) Semi and unstructured problems Support managers at all levels Support individual groups

6. Five types decision support system(DSS). 1.Data Driven DSS 2. Model 3.Knowledge 4.Document 5.Communication

7. Advantage of decision support Time saving Competitive advantage Cost Reduction

8. business and decision support To succeed, companies need information systems that can support the diverse information and decision-making needs of their managers and business professionals. Information, Decisions, & Management – The type of information required by decision makers is directly related to the level of management and the amount of structure in the decision situations

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10. Conti.. Information Quality – Timeliness Provided WHEN it is needed Up-to-date when it is provided Provided as often as needed Provided about past, present, and future time periods as necessar – Content Free from errors Should be related to the information needs of a specific recipient for a specific situation Provide all the information that is needed Only the information that is needed should be provided Can have a broad or narrow scope, or an internal or external focus Can reveal performance

11. Management Information Systems The original type of information system Produces many of the products that support day-to-day decision-making These information products typically take the following forms: – Periodic scheduled reports – Exception reports – Demand reports and responses – Push reports

12. Management reporting alternatives – Periodic scheduled reports Prespecified format Provided on a scheduled basis – Exception reports Produced only when exceptional conditions occur Reduces information overload – Demand reports and responses Available when demanded. Ad hoc – Push reports Information is sent to a networked PC over the corporate intranet. Not specifically requested by the recipient Conti…

13. Online Analytical Processing Enables managers and analysts to interactively examine & manipulate large amounts of detailed and consolidated data from many perspectives – Analyze complex relationships to discover patterns, trends, and exception conditions – Real-time Involves.. – Consolidation The aggregation of data. From simple roll-ups to complex groupings of interrelated data – Drill-Down Display detail data that comprise consolidated data

14. Conti… – Slicing and Dicing The ability to look at the database from different viewpoints. When performed along a time axis, helps analyze trends and find patterns

15. Computer-based information systems that provide interactive information support during the decision-making process DSS’s use – Analytical models – Specialized databases – The decision maker’s insights & judgments – An interactive, computer-based modeling process to support making semistructured and unstructured business decisions Designed to be ad hoc, quick-response systems that are initiated and controlled by the decision maker DSS Models and Software – Rely on model bases as well as databases – Might include models and analytical techniques used to express complex relationships Decision Support Systems

16. Using Decision Support Systems An interactive modeling process Four types of analytical modeling – What-if analysis – Sensitivity analysis – Goal-seeking analysis – Optimization analysis What-If Analysis – End user makes changes to variables, or relationships among variables, and observes the resulting changes in the values of other variables

17. Conti…. Sensitivity Analysis – A special case of what-if analysis – The value of only one variable is changed repeatedly, and the resulting changes on other variables are observed – Typically used when there is uncertainty about the assumptions made in estimating the value of certain key variables Goal-Seeking Analysis – Instead of observing how changes in a variable affect other variables, goal-seeking sets a target value (a goal) for a variable, then repeatedly changes other variables until the target value is achieved

18. Executive Information Systems EIS’s combine many of the features of MIS and DSS Originally intended to provide top executives with immediate, easy access to information about the firm’s “critical success factors” Alternative names – Enterprise information systems – Executive support systems Features of an EIS – Information presented in forms tailored to the preferences of the users – Most stress use of graphical user interface and graphics displays – May also include exception reporting and trend analysis

19. IT that helps gather, organize, and share business knowledge within an organization Hypermedia databases that store and disseminate business knowledge. May also be called knowledge bases Best practices, policies, business solutions Entered through the enterprise knowledge portal Knowledge Management Systems

20. Section II  Artificial intelgence thecnologies in bussines  Artificial intelligence  Neural network  Virtual reality  Intelligent Agents  Expert system  Developing expertsystems

21. A field of science and technology based on disciplines such as computer science, biology, psychology, linguistics, mathematics, & engineering Goal is to develop computers that can think, see, hear, walk, talk, and feel Major thrust – development of computer functions normally associated with human intelligence – reasoning, learning, problem solving

22. Domains of AI – Three major areas Cognitive science Robotics Natural interfaces Cognitive science – Focuses on researching how the human brain works & how humans think and learn – Applications Expert systems Adaptive learning systems Fuzzy logic systems Neural networks Intelligent agents

23. Conti.. Robotics – Produces robot machines with computer intelligence and computer controlled, humanlike physical capabilities Natural interfaces – Natural language and speech recognition – Talking to a computer and having it understand – Virtual reality

24. Neural Networks Computing systems modeled after the brain’s meshlike network of interconnected processing elements, called neurons Goal – the neural network learns from data it processes

25. Virtual Reality Computer-simulated reality Relies on multisensory input/output devices Allows interaction with computer-simulated objects, entities, and environments in three dimensions

26. Intelligent Agents A “software surrogate” for an end user or a process that fulfills a stated need or activity Uses built-in and learned knowledge base about a person or process to make decisions and accomplish tasks

27. Expert Systems A knowledge-based information system that uses its knowledge about a specific, complex application area to act as an expert consultant Provides answers to questions in a very specific problem area Must be able to explain reasoning process and conclusions to the user

28. Conti… Components Knowledge base Software resources Knowledge base Contain Facts about a specific subject are Heuristics that express the reasoning procedures of an expert on the subject

29. Conti.. Software Resources – Contains an inference engine and other programs for refining knowledge and communicating » Inference engine processes the knowledge, and makes associations and inferences » User interface programs, including an explanation program, allows communication with user

30. Developing Expert Systems Begin with an expert system shell Add the knowledge base Built by a “knowledge engineer” – Works with experts to capture their knowledge – Works with domain experts to build the expert system