Course Outline DECISION SUPPORT SYSTEMS Abraham Otero Abraham Otero DECISION SUPPORT SYSTEMS 1/11 This course Course Outline Describes the decision making process Describes the architecture of a decision support system (DSS) Presents the techniques most commonly employed in the construction of decision support systems, and in making decisions with the support of the system. Presents the problems related to decision support systems that are not yet resolved satisfactorily at present and, therefore, are open research areas Abraham Otero DECISION SUPPORT SYSTEMS 2/11 1
Course Outline More specifically, after finishing this course, students will: Understand the process of decision making and each of its phases Understand the general architecture of a DSS Design a DSS Have criteria to evaluate the various options to build a DSS Know the challenges and possible solutions that may arise during the construction of the data subsystem of a DSS Abraham Otero DECISION SUPPORT SYSTEMS 3/11 Course Outline More specifically, after finishing this course, students will: Understand the functionality, pros and cons of the possible components (models) that can be used in the model subsystem of a DSS Identify problems and possible solutions related to the dialogue subsystem of a DSS Know the problems that are commonly faced by DSS users Know the problems that are still not resolved in the field of DSS and, therefore, they are open research fields Abraham Otero DECISION SUPPORT SYSTEMS 4/11 2
Agenda Introduction Introduction Computerized Decision Support DSS architecture BI and DSS DSS life cycle Decision making Decision making Phases of the decision process The intelligence phase The design phase The choice phase Implementation phase How decisions are supported Abraham Otero DECISION SUPPORT SYSTEMS 5/11 Agenda DSS architecture DSS Characteristics and Capabilities DSS architecture Data Management Subsystem The Dialog (User Interface) Subsystem Other components Data Management Subsystem The database Why do I need a data warehouse? Data warehouse architecture Exploring a data warehouse Data warehouse implementation ETL systems Data preparation Real-time data warehousing Abraham Otero DECISION SUPPORT SYSTEMS 6/11 3
Agenda About models About models Mathematical programming Regression Influence diagram Decision Tree Introduction to Artificial Intelligence Introduction to Artificial Intelligence Search problems Fuzzy logic Neural Networks Genetic algorithms Bioinspired Computation Abraham Otero DECISION SUPPORT SYSTEMS 7/11 Agenda Expert systems Introduction Expert systems architecture Inference engines strategies Data Mining Data Mining Overview Building a decision tree Rule systems Association rules Clustering Bayesian networks Abraham Otero DECISION SUPPORT SYSTEMS 8/11 4
Agenda Other topics related to the model subsystem Sensitivity analysis Model evaluation Guidelines for method selection Model management The dialog subsystem Functions of the dialog subsystem Usability Some design guidelines Interaction Modalities Typical user complaints Intelligent user interface Future trends Abraham Otero DECISION SUPPORT SYSTEMS 9/11 We will apply the theoretical concepts of the course to build an expert system using CLIPS. Practice Abraham Otero DECISION SUPPORT SYSTEMS 10/11 5
On the shoulders of giants Thanks to Efraim Turban, Jay E. Aronson, Ting- Peng Liang and Ramesh Sharda for the support materials of their book "Decision Support and Business Intelligence Systems" John M. Gallaugher for his interesting case studies Joseph C. Giarratano for the CLIPS user's guide Kathryn Blackmond Laskey for his course Decision Support Systems Engineering Lucy Hederman for his course in expert systems The authors of more websites than I can remember Abraham Otero DECISION SUPPORT SYSTEMS 11/11 6