Decision Support Systems

Similar documents
Computerized Decision Support

Decision Support and Business Intelligence Systems. Chapter 1: Decision Support Systems and Business Intelligence

Decision Support Framework for BIS

Chapter 1 DECISION SUPPORT SYSTEMS AND BUSINESS INTELLIGENCE

Anale. Seria Informatică. Vol. VII fasc Annals. Computer Science Series. 7 th Tome 1 st Fasc. 2009

DECISION SUPPORT SYSTEMS OR BUSINESS INTELLIGENCE: WHAT CAN HELP IN DECISION MAKING?

DECISION SUPPORT SYSTEMS IN INFORMATION TECHNOLOGY ASSIMILATION

Ezgi Dinçerden. Marmara University, Istanbul, Turkey

Cis330. Mostafa Z. Ali

STATE UNIVERSITY OF NEW YORK COLLEGE OF TECHNOLOGY CANTON, NEW YORK MINS/CITA 315. Decision Support Systems

A Decision Support System for Agriculture Using Natural Language Processing (ADSS)

IMPROVING THE QUALITY OF THE DECISION MAKING BY USING BUSINESS INTELLIGENCE SOLUTIONS

A DECISION SUPPORT SYSTEM FOR THE LEVEL OF REPAIR ANALYSIS PROBLEM. Carlos M. Ituarte-Villarreal and Jose F. Espiritu

Ilishan-Remo, Ogun State, Nigeria

Evolution of Information System

Course Syllabus Business Intelligence and CRM Technologies

Hybrid Support Systems: a Business Intelligence Approach

SISINF - Information Systems

BUSINESS INTELLIGENCE

Business Intelligence and Decision Support Systems

Chapter 5 Business Intelligence: Data Warehousing, Data Acquisition, Data Mining, Business Analytics, and Visualization

COURSE PROFILE. Business Intelligence MIS531 Fall

Management Information Systems

THE INTELLIGENT BUSINESS INTELLIGENCE SOLUTIONS

Identifying BI Opportunities and BIS Development Process

INTELLIGENT DECISION SUPPORT SYSTEMS FOR ADMISSION MANAGEMENT IN HIGHER EDUCATION INSTITUTES

SYLLABUS. 1 seminar/laboratory 3.4 Total hours in the curriculum 42 Of which: 3.5 course

BN2231 DECISION SUPPORT SYSTEMS

Improving Decision Making and Managing Knowledge

Chapter 8. Generic types of information systems. Databases. Matthew Hinton

Animation. Intelligence. Business. Computer. Areas of Focus. Master of Science Degree Program

Business Intelligence and Analytics SCH-MGMT 553 (New course number being proposed) Tu/Th 11:15 AM 12:30 PM in SOM Lab 20

Class 2. Learning Objectives

INTERACTIVE DECISION SUPPORT SYSTEM BASED ON ANALYSIS AND SYNTHESIS OF DATA - DATA WAREHOUSE

Data Warehouse Architecture Overview

COURSE SYLLABUS. Enterprise Information Systems and Business Intelligence

Chapter 9 Knowledge Management

CONTEMPORARY DECISION SUPPORT AND KNOWLEDGE MANAGEMENT TECHNOLOGIES

A Study on Integrating Business Intelligence into E-Business

Facultatea de Business Str. Horea nr. 7 Cluj-Napoca, RO Tel.: Fax: tbs@tbs.ubbcluj.ro

SYLLABUS. Computer Science - romanian. 1 lab seminar/laboratory 3.4 Total hours in the curriculum 36 Of which: 3.5 course


A Knowledge Management Framework Using Business Intelligence Solutions

DETERMINATION AND INVESTIGATION OF INFORMAITION TECHNOLOGY PARAMETERS EFFECTIVE TO FOOD INDUSTRY DEVELOPMENT

Information Systems and Technologies in Organizations

THE ROLE OF BUSINESS INTELLIGENCE IN BUSINESS PERFORMANCE MANAGEMENT

DESIGNING THE ANALYSIS REPORTS BY MEANS OF THE BI INSTRUMENTS

LUCRĂRI ŞTIINŢIFICE, SERIA I, VOL. XII (2) BUSINESS INTELLIGENCE TOOLS AND THE CONCEPTUAL ARCHITECTURE

Course DSS. Business Intelligence: Data Warehousing, Data Acquisition, Data Mining, Business Analytics, and Visualization

CHAPTER 12. Business Intelligence

CONCEPTUALIZING BUSINESS INTELLIGENCE ARCHITECTURE MOHAMMAD SHARIAT, Florida A&M University ROSCOE HIGHTOWER, JR., Florida A&M University

Enterprise Information Systems

ระบบธ รก จอ จฉร ยะและการว เคราะห ทางการตลาด

Enhancing Decision Making

BENEFITS AND ADVANTAGES OF BUSINESS INTELLIGENCE IN CORPORATE MANAGEMENT

The Role of Management Information System (MIS) and Decision Support System (DSS) for Manager s Decision Making Process

SYLLABUS. Academic year

Business Process Management Systems and Business Intelligence Systems as support of Knowledge Management

Chapter Managing Knowledge in the Digital Firm

BUSINESS INTELLIGENCE AS SUPPORT TO KNOWLEDGE MANAGEMENT

Chapter 13: Knowledge Management In Nutshell. Information Technology For Management Turban, McLean, Wetherbe John Wiley & Sons, Inc.

NECESSITY TO IMPLEMENT A BUSINESS INTELLIGENCE SOLUTION FOR THE MANAGEMENT OPTIMIZATION OF A COMPANY

SYLLABUS Prerequisites (if necessary) 4.1 curriculum competencies Good to advanced user of office programmes

Data management. Data Life Cycle Process

Using Business Intelligence techniques to increase the safety of citizens The Tilburg case. Abstract

Business Information Systems. IT Enabled Services And Emerging Technologies. Chapter 4: Facilitated e-learning Part 1 of 2 CA M S Mehta, FCA

PG CERTIFICATE IN INFORMATION TECHNOLOGY MANAGEMENT (CASME&T)

STATE UNIVERSITY OF NEW YORK COLLEGE OF TECHNOLOGY CANTON, NEW YORK CITA/MINS 300. Management Information Systems

Optimizing Data Warehousing Strategies

Decision making based on Management Information System and Decision Support System

DECISION SUPPORT SYSTEM IS A TOOL FOR MAKING BETTER DECISIONS IN THE ORGANIZATION

A collaborative approach of Business Intelligence systems

Chapter I: Supporting Business Decision-Making

Information Systems for Business Operations

CHAPTER 12. Business Intelligence

CHAPTER OUTLINE LEARNING OBJECTIVES 8/14/2012. Business Intelligence

5.5 Copyright 2011 Pearson Education, Inc. publishing as Prentice Hall. Figure 5-2

Course Code CE609. Lecture : 03. Practical : 01. Course Credit. Tutorial : 00. Total : 04. Course Learning Outcomes

Conceptual Integrated CRM GIS Framework

Application of Information Systems in Electronic Insurance

STRATEGIC AND FINANCIAL PERFORMANCE USING BUSINESS INTELLIGENCE SOLUTIONS

Delivering Smart Answers!

Business Intelligence: Effective Decision Making

Chapter 5. Warehousing, Data Acquisition, Data. Visualization

How To Get A Computer Engineering Degree

Increasing the Business Performances using Business Intelligence

CHAPTER SIX DATA. Business Intelligence The McGraw-Hill Companies, All Rights Reserved

Part I: Decision Support Systems

ARTICLES VINE 37,4. The current issue and full text archive of this journal is available at

Data Mining and Business Intelligence CIT-6-DMB. Faculty of Business 2011/2012. Level 6

Knowledge Management

A review of frameworks for classification of information systems, notably on the Anthony s Triangle

Australian School of Business School of Information Systems Technology and Management. INFS5991/4891 Business Intelligence and Decision Support

Chapter 1 The Systems Development Environment

KEMI-TORNIO UNIVERSITY OF APPLIED SCIENCES

DSS for academic workload management

RYERSON UNIVERSITY Ted Rogers School of Information Technology Management And G. Raymond Chang School of Continuing Education

New Trends in Business Intelligence A Case Study

DASHBOARD TECHNOLOGY BASED SOLUTION TO DECISION MAKING

Important dimensions of knowledge Knowledge is a firm asset: Knowledge has different forms Knowledge has a location Knowledge is situational Wisdom:

Transcription:

C_1 / 30.09.2014 Decision Support Systems Cod Denumire Ore: C+S+L+P Finalizare Credite MID1009 Sisteme pentru fundamentarea deciziilor 2+1+0+1 E 8 cr. Marti 16-18 S2 L320 Sem. 18-20 Curs Mail: per@cs.ubbcluj.ro, Web: www.cs.ubbcluj.ro/~per Dss: http://www.cs.ubbcluj.ro/~per/dss.html 1/21

Course objectives 7.1 General objective of the discipline 7.2 Specific objective of the discipline Good understanding of hands-on applications; Be able to identify meaningful applied computing problems ; Be able to apply theories, principles and concepts with technologies to design, develop, and verify computational solutions; Knowledge about general theory and specific DSS theory; Systematic knowledge about what the designer of a DSS needs to know; 2/21

Course contents: 1. The concept of Decision Support Systems (DSS) - The Steps of Decision Support, Classification of Problems - The Components of a DSS. - Some Computerized Tools for Decision Support 2. Computerized Decision Support - Decision Making - Rational Decisions, Definitions of Rationality, Bounded Rationality and Muddling Through - Models, The Facilities of Models, Phases of the Decision-Making Process 3. The Nature of Managers, Appropriate Data Support, Information Processing Models. Group Decision Making 4. Decisions and Decision Modeling - Types of Decisions. - Human Judgment and Decision Making. - Modeling Decisions. Components of Decision Models 3/21

Course contents: 5. Normative Systems - Normative and Descriptive Approaches. - Decision-Analytic Decision Support Systems. - Equation-Based and Mixed Systems 6. Data Component - Characteristics of Information. - Databases to Support Decision Making. - Database Management Systems 7. Data Warehouses. - Data Mining and Intelligent Agents 8. Model Component - Models, Representation, Methodology 9. Model Based Management Systems, Access to Models, and Understandability of Results. - Integrating Models, Sensitivity of a Decision 4/21

Course contents: 10. Intelligence and Decision Support Systems - Programming Reasoning - Backward Chaining Reasoning and Forward Chaining Reasoning. 11. Knowledge Representation for Decision Support Systems - Computational Intelligence for Decision Support, - Expert Systems and Artificial Intelligence in Decision Support Systems 12. User Interfaces to Decision Support Systems. - Support for Model Construction and Model Analysis. - Support for Reasoning about the Problem Structure in Addition to Numerical Calculations. - Support for Both Choice and Optimization of Decision Variables 13. Graphical Interface - The Action Language, Menus. Mail Component - Integration of Mail Management. - Implications for DSS Design 14. Visualization in Decision Support Systems - Visualization User Interface for Decision Support Systems 5/21

Total estimated time (hours/semester of didactic activities) Hours per week 3 Of which: 2 course Total hours in the curriculum 42 Of which: 5 course Time allotment: 2 seminar/laboratory 1 / - 28 seminar/laboratory 14 / - Learning using manual, course support, bibliography, course notes 36 Additional documentation (on electronic platforms, field documentation, ) 36 Preparation for seminars/labs, homework, papers, portfolios and essays 36 Tutorship 18 Evaluations 18 Other activities: Project 14 Total individual study hours 158 Total hours per semester 200 Number of ECTS credits 8 hours 6/21

R_Bibliography: 1. Filip F.G. (2005), Decizie asistata de calculator: decizii, decidenti, metode de baza si instrumente informatice asociate, (Editia doua completata si revizuita a lucrarii din 2002), Ed. TEHNICA, Bucuresti, ISBN 973-31-2254-8, XXVIII + 376 pag. (http://www.academiaromana.ro/carti2005/c0414_ffilip.htm ) 2. Filip, F.G. (2007). Sisteme suport pentru decizii. (Editia II revazuta si adaugita a lucrarii din 2004), Ed. TEHNICA, Bucuresti (ISBN978-973-31-2308-8), XI + XIX + 372 pag. (http://www.acad.ro/carti2007/carte07_02ff.htm ). 7/21

E_Bibliography: 1. Alter, S. L. Decision support systems: current practice and continuing challenges. Reading, Mass., Addison-Wesley Pub., 1980. 2. Finlay, P. N., Introducing decision support systems. Oxford, UK Cambridge, Mass., NCC Blackwell; Blackwell Publishers, 1994. 3. Marakas, G.M. Decision Support Systems in the 21st Century. Prentice Hall, Upper Saddle River, NJ, 2003. 4. Moore, J.H.,and M.G.Chang.Design of Decision Support Systems" Data Base,Vol.12, Nos.1 and 2. Fall, 1980. 5. Power, D. J. Decision support systems: concepts and resources for managers. Westport, Conn., Quorum Books, 2002. 6. Power, D. J. Web-based and model-driven decision support systems: concepts and issues. Proceedings of the Americas Conference on Information Systems, Long Beach, California, 2000. 7. Sauter, V. L. Decision support systems: an applied managerial approach. New York, John Wiley, 1997. 8. Silver, M. Systems that support decision makers: description and analysis. Chichester ; New York, Wiley, 1991. 9. Sprague, R. H. and E. D. Carlson. Building effective decision support systems. Englewood Cliffs, N.J., Prentice-Hall, 1982, ISBN 0-130-86215-10. Turban, E.,Aronson, J.E., and Liang, T.P. Decision Support Systems and Intelligent Systems. New Jersey, Pearson Education, Inc, 2005. See: http://www.cs.ubbcluj.ro/~per/dss.html 8/21

Assessment Evaluation: Type of activity Evaluation criteria Evaluation methods Share in the grade Course Seminar / Project - know the basic elements and concepts of an Dss; - complexity, importance and degree of timeliness of the synthesis made - apply the course concepts - problem solving Written exam 50% Paper presentation Project presentation 15% 35% Minimum performance standards At least grade 5 at written exam, paper presentations and project realised. 9/21

Additional references: 1. French, S. and Geldermann, J. The varied contexts of environmental decision problems and their implications for decision support. Environmental Science and Policy 8 (2005), 378 391. 2. Gadomski, A.M. at al.an Approach to the Intelligent Decision Advisor (IDA) for Emergency Managers.Int. J. Risk Assessment and Management, Vol. 2, Nos. 3/4., 2001. 3. Hackathorn, R. D., and P. G. W. Keen. (1981, September). "Organizational Strategies for Personal Computing in Decision Support Systems." MIS Quarterly, Vol. 5, No. 3. 4. Holsapple, C.W., and A. B. Whinston. (1996). Decision Support Systems: A Knowledge-Based Approach. St. Paul: West Publishing. ISBN 0-324-03578-0 5. Jiménez, Antonio; Ríos-Insua, Sixto; Mateos, Alfonso. Computers & Operations Research. 6. Joyce E. Berg, Thomas A. Rietz, Prediction Markets as Decision Support Systems, Kluwer Academic Publishers. Manufactured in The Netherlands, 2003. 7. Keen, P. G. W. (1978). Decision support systems: an organizational perspective. Reading, Mass. 10/21

Additional references: 8. Keen, P. G. W. (1980). Decision support systems: a research perspective. Decision support systems : issues and challenges. G. Fick and R. H. Sprague. Oxford ; New York, Pergamon Press. 9. Larissa T. Moss, Shaku Atre, Business Intelligence Roadmap: The Complete Project Lifecycle for Decision-Support Applications By Publisher: Addison Wesley Professional Pub Date: February 25, 2003 Print ISBN-10: 0-201-78420-3 Print ISBN-13: 978-0-201-78420-6 Pages: 576 Slots: 2.0 10.Little, J.D.C. "Models and Managers:The Concept of a Decision Calculus." Management Science, Vol.16,NO.8, April, 1970. 11.Sauter, V.L. Decision Support Systems: An Applied Managerial Approach, New York: John Wiley & Sons, 1997. 12.Sprague, R. H. and H. J. Watson. Decision support systems: putting theory into practice. Englewood Clifts, N.J., Prentice Hall, 1993. 13.Turban, E. and Aronson, J.E. Decision Support Systems and Intelligent Systems, Prentice Hall, Upper Saddle River, NJ, 2001, ISBN-0-13-089465-6 14.Weick, K.E. and Sutcliffe, K. Managing the Unexpected: Assuring High Performance in an Age of Complexity. Jossey Bass, San Francisco, CA, 2001. 11/21

Additional references: 15.Delic, K.A., Douillet,L. and Dayal, U. "Towards an architecture for real-time decision support systems:challenges and solutions, 2001. 16.Druzdzel, M. J. and R. R. Flynn. Decision Support Systems. Encyclopedia of Library and Information Science. A. Kent, Marcel Dekker, Inc., 1999 17.Gachet, A. Building Model-Driven Decision Support Systems with Dicodess. Zurich, VDF, 2004. 18.Marakas, G. M. Decision support systems in the twenty-first century. Upper Saddle River, N.J., Prentice Hall, 1999. 19.Power, D.J. A Brief History of Decision Support Systems DSSResources.COM, World Wide Web, version 2.8, May 31, 2003. 20.Reich, Yoram; Kapeliuk, Adi. Decision Support Systems., Nov2005, Vol. 41 Issue 1, p1-19, 19p. 21.Decision Support Systems. Elsevier B.V., 2007. [http://www.sciencedirect.com/science/journal/01679236] 22.Turban, E., Aronson, J.E., Linag, T., Sharda, R, Decision Support and Business Intelligent Systems, Prentice Hall, Upper Saddle River, NJ, 8 th ed. 2007, ISBN- 0-13-198660-0. 12/21

1. Introduction The Decision Support Systems are used because they have the following properties: Speedy computation: enables many computations quickly at a low cost; the speed of executions increasing every day ; Improved communication and collaboration: decisions are made by groups from different locations (travel costs); Increased productivity of group members: using software optimization tools to find the best solution; Improved data management: store, search, transmit data (text, sound, graphics, video even in foreign languages) quickly, securely, and so on; Managing giant data warehouse great storage capability of any type of information that can be accessed and searched very rapidly (parallel computing); [22] -Decision Support System and Business Intelligence Turban, E., 13/21

1. Introduction Quality support : improve the quality of decisions made more alternatives can be evaluated, (can be performed) quick(ly) risk analysis using simulations, artificial intelligence methods, ; Agility support : intelligent systems allow to make good and quick decisions; Overcoming cognitive limits in processing and storing information : computerized systems enable to overcome the cognitive limits by quickly accessing and processing stored information; Using the Web : access to a vast body of data, information, knowledge, user-friendly graphical user interface GUI, collaboration with remote partners, intelligent search tools to find quickly any information; Anywhere, anytime support : using wireless technology, we can access information anytime and from anyplace and communicate the result of the analysis and interpretation. 14/21

1.1. The Steps of Decision Support Simon (1977): the decision-making process is a 4-phase process: Intelligence: searching for conditions that call for decisions; Design: inventing, developing, analyzing solutions; Choice: selecting a course of action; Implementation: adapting the selected course of action; Implementation Put solution into action Problem or opportunity Choice Compare and select Intelligence Environment, reports Design Alternatives, Solutions 15/21

1.2. Classification of Problems The decision-making process may be range from highly structured (programmed - with standard solution methods, because is possible to abstract, analyze, and classify into specific categories for which we have a model and a solution management science (MS) / operation research (OR) ) to highly unstructured (non-programmed- fuzzy, complex problems there are no cut and dried solution methods). Definitions: An unstructured problem: all phases are unstructured, A structured problem: all phases are structured, the procedures for obtaining the best solution are known, Semi structured problem: has structured and also unstructured phases. 16/21

1.3. What is a DSS? - The concept of Decision Support Systems (DSS) Scott Morton (~1970) defined the major concepts of Decision Support Systems. Gorry and Scott-Morton (1971) : Interactive computer-based systems, which help decision maker utilize data and model to solve unstructured problems. Keen and Scott-Morton (1978) : Decision support system couple the intellectual resources of individuals with the capabilities of the computer to improve the quality of decisions. It is a computerbased support system for management decision makers who deal with semi-structured problems. DSS can be used to describe any computerizing system that supports decision making in an organization. Observation: Decision Support System Management Information System (MIS). 17/21

1.4. The Components of a DSS - The Architecture of DSS The term DSS can be use to refer to the DSS application. 1. Every problem requires Data from many sources; 2. Data are manipulated by using Models (standard or customized); 3. Systems sometimes have a Knowledge or intelligence component; 4. Users are another important component; 5. The User interface is the last component of the DSS architecture. Data Models Knowledge User interface User 18/21

1.5. Some Computerized Tools for Decision Support Data management DBMS - Databases and database management system; ETL - Extraction, transformation and load system; DW - Data warehouses, real-time DW and data marts; Reporting status tracking OLAP - Online analytical processing; EIS - Executive information system; Visualization GIS - Geographical information system; - Dashboards; Information portals; Multidimensional presentation; Business analytics - Optimization; Web analytics; - Data mining, Web mining and text mining; Strategy and performance management B(C)PM- Business (Corporate) performance management; BAM - Business activity management; - Dashboards and scorecards; 19/21

Some Computerized Tools for Decision Support Communication and collaboration GDSS - Group decision support system; GSS - Group support system; - Collaborative information portals and system; Knowledge management KMS - Knowledge management systems; - Expert locating system; Intelligent systems ES - Expert systems; ANN - Artificial neural networks; - Fuzzy logic, Genetic algorithm, Intelligent agents; ADS - Automated decision systems; Enterprise systems ERP CRM SCM - Enterprise resource planning; - Customer relationship management; - Supply-chain management; 20/21

1.6. Why companies (want to) use Computerized Decision Support? Changing economy; Many business operations; Global competition; E-commerce; For decisions making; Solve directly the management s inquiries without Inf. Sys. Depart.; Need a special analysis of profitability and efficiency; Need an accurate information; Computerizing support is viewed as an organizational winner; Need new information; Need higher decision quality; Desire improved communication; Want improve customer and employee satisfaction; Need timely information; Want to reduce costs; Want to see improved productivity. 21/21

End of 1. Seminar (Laboratory): the planning of the papers and projects. How many students? n How many papers/lab (2 weeks)? n/5 When? For each student! (~What?) Paper Project To do a Calendar 1-2; 3-11, 13-14 (2,9,2) = 9 hours Alphabetical? Individually or in groups of 2,3, students??... C_1 / 30.09.2013 22/21