1. Chapter 7: Business Intelligence and Decision Support Copyright © 2013 Pearson Education, Inc. publishing as Prentice Hall Chapter 7 - 1

2. Learning objectives 1.Decision making 2.Business intelligence 3.Data mining 4.Web analytics 5.Dashboards and portals Copyright © 2013 Pearson Education, Inc. publishing as Prentice Hall Chapter 7 - 2

3. Police department Data mining to deploy officers 47% decline in complaints 246% increase in recovered weapons $15,000 HR savings during shift Copyright © 2013 Pearson Education, Inc. publishing as Prentice Hall Chapter 7 - 3

4. Business intelligence Information for data-driven decision making Includes software applications, technologies, and practices Copyright © 2013 Pearson Education, Inc. publishing as Prentice Hall Chapter 7 - 4

5. Levels of decision making Strategic Tactical Operational Copyright © 2013 Pearson Education, Inc. publishing as Prentice Hall Chapter 7 - 5

6. InternalExternal Transactional databases Data warehouses Cloud External databases Web sites, social networks, and text messages Copyright © 2013 Pearson Education, Inc. publishing as Prentice Hall Chapter 7 - 6 BI sources

7. Analyzing patterns Online analytical processing Statistics and modeling techniques Text mining Copyright © 2013 Pearson Education, Inc. publishing as Prentice Hall Chapter 7 - 7

8. Simulating and forecasting What-if analysis Goal seeking and optimization Forecasting Copyright © 2013 Pearson Education, Inc. publishing as Prentice Hall Chapter 7 - 8

9. ExamplesChallenge Amazon.com ALADDIN Jeopardy! Scammers CAPTCHA Copyright © 2013 Pearson Education, Inc. publishing as Prentice Hall Chapter 7 - 9 Artificial intelligence

10. Artificial intelligence applications Robotics Expert systems Neural nets Copyright © 2013 Pearson Education, Inc. publishing as Prentice Hall Chapter 7 - 10

11. Web analytics Website Social media E-commerce Copyright © 2013 Pearson Education, Inc. publishing as Prentice Hall Chapter 7 - 11

12. Analyzing traffic Analyzing software Reaching goals Ad effectiveness Copyright © 2013 Pearson Education, Inc. publishing as Prentice Hall Chapter 7 - 12

13. Dashboards Graphical user interface Key performance indicators Copyright © 2013 Pearson Education, Inc. publishing as Prentice Hall Chapter 7 - 13

14. Portals Variety of information on one screen Enterprise portal Copyright © 2013 Pearson Education, Inc. publishing as Prentice Hall Chapter 7 - 14

15. Mashups Aggregate data from multiple sources Customizable web pages Copyright © 2013 Pearson Education, Inc. publishing as Prentice Hall Chapter 7 - 15

16. Human element Although humans choose intelligence, tools and interpretation, they have weaknesses Must consider human motives in design and implementation of information systems Copyright © 2013 Pearson Education, Inc. publishing as Prentice Hall Chapter 7 - 16

17. Summary 1.Decision making 2.Business intelligence 3.Data mining 4.Web analytics 5.Dashboards and portals Copyright © 2013 Pearson Education, Inc. publishing as Prentice Hall Chapter 7 - 17

18. Insurance Fraud case $68 billion lost in fraud each year Fraud detection systems rely on rules and patterns detected by analytic engines Analysts work closely with investigators to apply human judgment as they create new rules and follow data leads Copyright © 2013 Pearson Education, Inc. publishing as Prentice Hall Chapter 7 - 18

19. New York Jets case Command Center—four-panel touch screen Real-time aggregated data Fan dashboard Copyright © 2013 Pearson Education, Inc. publishing as Prentice Hall Chapter 7 - 19

20. Copyright © 2013 Pearson Education, Inc. publishing as Prentice Hall Chapter 7 - 20