1. CHAPTER 12 & Tech Guide 4 Business Intelligence & Intelligent Systems

2. Announcements Class Today Chapter 12 – Business Intelligence Business Intelligence Case Tech Guide 4 – Intelligent Systems Fri. & Mon. Class Decision Support Case

3. CLASS OUTLINE Managers and Decision Making What Is Business Intelligence? BI Applications for Data Analysis BI Presenting Results BI Case Intelligent Systems

4. Chapter 11 Review Customer Relationship Management Why do we need CRM? Operational CRM Analytical CRM Supply Chain Management Solutions through IS EDI and Extranets

5. Opening Information Opening Clip: What is BI and Analytics? http://www.youtube.com/watch?v=0aHtHl-jcAs Lenovo Story http://www.youtube.com/watch?v=v6wZMa75T l8 http://www.youtube.com/watch?v=v6wZMa75T l8 Hana Academy

6. Now that we capture all this info…. What do we do with it? Managers have three basic roles Interpersonal roles Informational roles Decisional roles Why do managers need IT support? Source: Media Bakery

7. Why Managers Need IT Support Number of alternatives Time pressures Complexity

8. Decision Analysis Problem Structure: Nature of Decision: Operational control Management control Strategic planning Highly structured Semistructured Highly unstructured Order entryLoan approvalDetermining a new Store location

9. What Is Business Intelligence?

10. How Business Intelligence Works? ERP CRM SCM Data Warehouse “Getting data in” “Getting data out”

11. Careers in Business Intelligence Entry Level: Business Intelligence Analyst Companies using BI IBM Global Services Deloitte Skills Needed Understanding the tools Database/SQL Basic Programming Analysis/Reporting Knowledge

12. The Scope of Business Intelligence Smaller organizations: Excel spreadsheets Larger organizations: Data mining, predictive analytics, dashboards

13. Finance DM How Organizations Use BI Enterprise-Wide Need Departmental Need DATA WAREHOUSE Sales DM Inventory/ Shipping DM

14. What can you do with Business Intelligence? Business Intelligence Applications Multidimensional Analysis or Online Analytical Processing (OLAP) Data Mining Decision Support Systems

15. Multidimensional Analysis or Online Analytical Processing (OLAP) “Slicing and dicing” data stored in a dimensional format, drilling down in greater detail and aggregating data.  Looks at what is happening or what has happened.  Quickly answer business questions

16. Data Mining Searching for information in a database, data warehouse, or data mart.  Predicting trends and behaviors  Identifying previously unknown patterns and relationships.

17. Decision Support Systems (DSS) Combine models and data in an attempt to solve semistructured/unstructured problems. DSS capabilities: Sensitivity analysis What-if analysis Goal-seeking analysis

18. Presenting BI Results: Digital Dashboards Digital Dashboards

19. Presenting BI Results: Data Visualization Data Visualization Technologies Geographic Information Systems Hans Rosling Ted Talk and Data VisualizationTed Talk Data Visualization

20. The Power of Visualization Even though a picture is “worth a thousand words,” we have to be very careful about just what we are seeing. Presenting BI Results

21. Presenting BI Results: Real-Time BI Enables users to employ multi-dimensional analysis, data mining and decision support systems to analyze data in real time. Example: FIGURE 12.7 1-8000 CONTACTS customer service agent dashboard.

22. Careers in Business Intelligence Entry Level: Business Intelligence Analyst Companies using BI IBM Global Services Deloitte Skills Needed Hot in Demand Area Analytical Ability allowing you to learn: Understanding the tools Database/SQL Basic Programming Analysis/Reporting Knowledge

23. Chapter Review Describe and provide examples of the three different ways in which organizations use business intelligence.

24. Chapter Review (cont.) Specify the BI applications available to users for data analysis, and provide examples of how each might be used to solve a business problem at your university.

25. Chapter Review (cont.) Describe three BI applications that present the results of data analyses to users, and offer examples of how businesses and government agencies can use each of these technologies.

26. TECH GUIDE 4 Intelligent Systems

27. Introduction to Intelligent Systems Intelligent systems Artificial intelligence (AI) © Luis Alonso Ocana/Age Fotostock America, Inc.

28. Introduction to Intelligent Systems Business Applications – IBM’s WatsonIBM’s Watson http://www.businessweek.com/stories/2010-09-21/artificial-intelligence-goes- mobilebusinessweek-business-news-stock-market-and-financial-advice

29. Expert Systems Expertise & Expert systems (ESs)

30. Expert Systems: Expertise Transfer from Human to Computer Four Activities Involved: Knowledge acquisition Knowledge representation Knowledge inferencing Knowledge transfer

31. Intelligent Agents Assists in performing repetitive tasks which use expert systems and fuzzy logic to create a seemingly intelligent behavior (aka “Bots”)

32. Intelligent Agents: Examples Information Agents Monitoring-and-Surveillance Agents User Agents

33. Tech Guide Review Differentiate between artificial intelligence and human intelligence. Define expert systems, and provide examples of their use.

34. Tech Guide Review (cont.) Define intelligent agents, and provide examples of their use.