Business Intelligence And Analytics Systems For Decision Support – About the Contributors Ramesh Sharda (M.B.A., Ph.D., University of Wisconsin-Madison) is the Director of the Graduate School of Business in the CEO Program and the Institute for Information Systems Research (IRIS), ConocoPhillips Chair in Technology Management, and A. Regents Professor of Management Science and Information Systems at Oklahoma State University (OSU) Spears School of Business. Nearly 200 articles describing his research have been published in major journals, including Operations Research, Management Science, Information Systems Research, Decision Support Systems, and Journal of MIS. He co-founded the AIS SIG on Decision Support Systems and Knowledge Management (SIGDSS). Dr. Sharda serves on several editorial boards, including the INFORMS Journal on Computing, Decision Support Systems, and ACM Transactions on Management Information Systems. He has written and edited several textbooks and research books, and is co-editor of several book series (Integrated Series in Information Systems, Operations Research/Computer Science Interfaces and Annals of Information Systems) with Springer. He is also currently the CEO of Teradata University Network. His current research interests are decision support systems, business analytics, and information overload management technologies. Dursun Delen (Ph.D., Oklahoma State University) is the Spears and Patterson Chair in Business Analytics, Director of Research at the Center for Health Systems Innovation, and Professor of Management Science and Information Systems at Oklahoma State University’s (OSU) Spears School of Business. ) Prior to his academic career, he worked for a private research and consulting firm, Knowledge Based Systems Inc., in College Station, Texas, as a researcher for five years, during which he managed a number of decision support and other information systems; Related research programs funded by federal agencies such as DoD, NASA, NIST, and DOE. Dr. Delen’s research has appeared in major journals including Decision Support Systems, Communications of the ACM, Computing and Operations Research, Computing in Industry, Journal of Production Operations Management, Artificial Intelligence in Medicine, Expert Systems with Applications, and others. Recently, he published four textbooks. Advanced Data Mining Techniques with Springer, 2008; Decision Support and Business Intelligence Systems with Prentice Hall, 2010. Business intelligence. managerial approach, with Prentice Hall, 2010. and Practical Text Mining, with Elsevier, 2012. He is frequently invited to national and international conferences on key topics related to Data/Text Mining, Business Intelligence, Decision Support Systems and Knowledge Management. He served as Principal Co-Chair of the 4th International Conference on Network Computing and Advanced Information Management (September 2-4, 2008, Seoul, South Korea), and regularly chairs tracks and mini-tracks at various information systems conferences. He is the Editor-in-Chief of the International Journal of Experimental Algorithms, Associate Editor of the International Journal of RF Technology and Journal of Decision Analysis, and a member of the editorial board of five other technical journals. His research and teaching interests are in data and text mining, decision support systems, knowledge management, business intelligence, and enterprise modeling. Ephraim Turban (M.B.A., Ph.D., University of California, Berkeley) is a visiting researcher at the Pacific Institute for Information Systems Management, University of Hawaii. Prior to that, he was employed at several universities, including the City University of Hong Kong; Lehigh University; Florida International University; California State University, Long Beach; Eastern Illinois University; and the University of Southern California. Dr. Turban is the author of over 100 published articles
Decision Support and Business Intelligence Systems provides the only comprehensive, up-to-date guide to today’s revolutionary management support systems technologies, showing how they can be used to make better decisions. The 10th edition focuses on Business Intelligence (BI) and analytics for business decision support in a simpler book.
Business Intelligence And Analytics Systems For Decision Support
PART I. DECISIONS OF PRESENTATION AND ANALYSIS. LEAD 1. Overview of Business Intelligence, Analytics and Decision Support 2. Decision Making Fundamentals and Technologies PART II. DESCRIPTIVE ANALYSIS 3. Data Warehousing 4. Business Reporting, Visual Management and Business Performance Analysis PART III. PREDICTIVE ANALYSIS 5. Data Mining 6. Predictive Modeling Techniques 7. Text Analytics, Text Mining and Sentiment Analysis 8. Web Analytics, Web Mining and Social Analytics PART IV. PRESCRITIVE ANALYSIS 9. Model-Based Decision Making. – Criteria systems 10. Modeling and analysis. Heuristic Search Methods and Simulation 11. Automated Decision Systems and Expert Systems 12. Knowledge Management and Collaborative Systems PART V: BIG DATA AND FUTURE DIRECTIONS FOR BUSINESS ANALYTICS. Emerging trends and future business intelligence and analysis; Decision Support Systems (10th ed.) Chapter 1: An Overview of Business Intelligence, A. analysis and decision support
Business Intelligence And Analytics (systems For Decision Support), Buku & Alat Tulis, Buku Pelajaran Di Carousell
2 Learning Objectives Understand today’s hectic business environment and describe how organizations survive and even excel in such an environment (solve problems and exploit opportunities) Understand the need for computer support for management decision making Understand the early framework of management decision making… (Contd…)
3 Learning Objectives Learn the conceptual basics of the DSS method Describe the BI method and concepts and relate them to DSS Understand the different types of analysis List the most important computer aided decision support tools.
4 Open Vignette… Magpie Sensing uses analytics to efficiently and securely manage the vaccine supply chain. Company Background Problem Proposed Solution and Results. Answer and discuss case questions…
Business Intelligence And Analytics: What Is The Difference?
5 Open Vignette… Healthcare cold chain is defined as a temperature-controlled supply chain that includes a system for transporting and storing vaccines and drugs. It consists of three main components: transport and storage equipment, trained personnel and efficient handling procedures. Most cold chain vaccines are usually stored at 2-8 degrees Celsius. Maintaining cold chain integrity is critical for healthcare product manufacturers.
6 Open Vignette… It’s a wireless, wireless temperature and humidity monitor that provides real-time location-aware cold chain transit of goods. Magpie Sensing solutions are based on rich analytical algorithms that use data collected from monitoring devices to improve the efficiency of cold chain processes and predict cold storage problems before they occur.
What information is provided by the descriptive analysis used on Magpie Sensing? What support is provided by the predictive analytics used in Magpie Sensing? How does prescriptive analysis help in making business decisions? In what ways can real-time information be communicated to affected users of the system? In what other situations might real-time monitoring applications be necessary?
Understand Today’s Turbulent Business Environment
Companies are moving aggressively towards computer support for their operations Business Intelligence Business Pressures – Answers – Support Model Business pressures are the result of today’s competitive business environment.
The environment in which organizations operate today is increasingly complex, creating opportunities and challenges. For example: globalization. Business environment factors: markets, consumer demands, technology and societal…
FACTOR DESCRIPTION Markets Intense competition Expanding global markets Thriving e-markets on the Internet Innovative marketing methods IT-supported outsourcing opportunities Need for real-time transaction demand Consumer request for customization Needs for quality, product variety and speed of delivery Customers are becoming powerful and less loyal Technology More innovations, new products and new services Increasing aging rates Increasing information overload Social networking, Web 2.0, and beyond Society Increasing government regulation and deregulation Workforce more diverse, older, and comprised of more women Top concerns for homeland security and terrorist attacks Need for Sarbanes-Oxley Act and other legislation related to reporting; Increasing social responsibility in companies Greater emphasis on sustainability
What Are Decision Support Systems? Sifting Data For Better Business Decisions
Be reactive, anticipatory, adaptive and proactive Managers can take action, for example by using strategic planning. Leverage new and innovative business models. Reorganize business processes. Participate in business alliances. Improve information systems of companies. … more [in your book]
One of the main goals of computerized decision support is to reduce the gap between an organization’s current performance and desired performance, as expressed in its mission, goals and objectives, and the strategy to achieve them.
Management is the process by which organizational goals are achieved through the use of resources. Input: resources Result. achievement of goals; measures of success; results/input management Decision making Decision making. choosing the best solution from two or more alternatives;
Business Intelligence In Decision Support Systems
Interpersonal 1. Figure 2. Leader 3. Contact Information 4. Monitor 5. Disseminator 6. Spokesperson Decision 7. Entrepreneur 8. Concern Manager 9. Resource Allocator 10. Negotiator
Managers typically make decisions by following a four-step process (ie, the scientific method) Define the problem (or opportunity) Build a model that describes the real problem. Identify possible solutions to the simulated problem and evaluate their solutions. Compare, select and suggest a possible solution to the problem.
Group communication and collaboration Improved data management Data warehouse management and big data analytics support;
Business Intelligence Tools You Need To Know
Degree of structure (Simon, 1977) Decisions are classified as highly structured (a.k.a. programmed) semi-structured Highly unstructured (a.k.a. unprogrammed) Types of control (Anthony, 1965) Strategic planning (high-level, long-term) Management control (tactical planning) Operational control
20 DSS The concept of DSS. interactive computer systems that help decision makers use data and models to solve unstructured problems (Gorry and Scott-Morton, 1971). quality of decisions. DS as an umbrella term The evolution of DS
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