1. Business Intelligence: Big Results with a Small Budget Jeff Pittges Assistant Professor Radford University www.radford.edu/~jpittges jpittges@radford.eduwww.radford.edu/~jpittges jpittges@radford.edu / 540-831-5175 Jeff Pittges Assistant Professor Radford University www.radford.edu/~jpittges jpittges@radford.eduwww.radford.edu/~jpittges jpittges@radford.edu / 540-831-5175

2. 2 Industry Background

3. 3 Going Global The following slides were presented by Paul Grossman at the February 2009 NCTC Technology & Toast ExportVirginia.org

4. 4 THE REAL WORLD POPULATION Source: www.world mapper.org

5. 5 THE REAL WORLD CONTAINER PORTS Source: www.world mapper.org

6. 6 THE REAL WORLD HIGH TECH EXPORTS1990 Source: www.world mapper.org

7. 7 THE REAL WORLD HIGH TECH EXPORTS 2002 Source: www.world mapper.org

8. 8 What If You could view your business like these maps of the world? You could identify trends and compare your business to your competitors with respect to the market? You could see opportunities?

9. 9 Business Intelligence A set of tools and techniques that help people and companies make better decisions

10. 10 2009 Gartner Prediction Because of lack of information, processes, and tools, through 2012, more than 35 per- cent of the top 5000 global companies will regularly fail to make insightful decisions about significant changes in their business and markets. http://en.wikipedia.org/wiki/Business_intelligence

11. 11 BI Technologies Data Warehousing OLAP Executive Dashboards Data Mining Decision Support Systems (DSS) Expert Systems

12. 12 Drowning in Data Starving for Information

13. 13 Data Warehousing

14. 14 Warehouses Report the Facts Who What When Where Why

15. 15 OnLine Analytical Processing The process of slicing and dicing data: –Drill Down –Drill Up –Drill Across OLAP

16. 16 OLAP Example Analyze quarterly sales –Expected 10% increase in revenue –Realized a 9.5% increase –Why did quarterly revenue fall short of expectations?

17. 17 Investigate the Facts Why were sales short of expectations? When –Compare sales in Q1 2005 to Q1 2006 What -- Product hierarchy Who -- Customers

18. 18 When Time Dimension Year Quarter Month Week Day

19. 19 Time Dimension

20. 20 Sales by Quarter Q1 ‘05Q1 ‘06 $100 $109.5  9.5% Quarter

21. 21 Drill Down into Department - Clothes - Electronics - Books What Product Hierarchy Category Brand Product Department

22. 22 Product Dimension 2005Q1 Q2 Q3 Q4 Q1 Q2 2006 T i m e Product BooksElectronicsClothes

23. 23 Sales By Department ClothesElectronicsBooks 10% 10.3% 10.4% 8.7% Q1 ‘06 Q1 ‘06 Q1 ‘06 Dept

24. 24 Drill Down into Books Product Hierarchy Category Brand Product Department

25. 25 Product Dimension

26. 26 Sales by Book Category 10% Novels 10.6% Textbooks Q1 ‘06 6.8% Q1 ‘06 Category

27. 27 Who Age group Gender Marital status Occupation Annual income Customer Dimension

28. 28 Drill Down into Age Group 10% 25 - 45 10.9% Q1 ‘06 4.2% Q1 ‘06 Under 2546 - 65 10.4% Q1 ‘06 Over 65 11.1% Q1 ‘06 Age

29. 29 Customer Dimension

30. 30 Analysis Sales of textbooks to customers under 25 (students) fell well short of expectations What should the company do? Increase advertisements and incentives for textbooks to students

31. 31 Executive Dashboards

32. 32 Monitoring Your Business Management by Objective (MBO) –Sales -- revenue targets –Customer Support -- customer satisfaction Key Performance Indicators (KPI) –Measure performance Dashboard Displays KPIs –Color coded Green Yellow Red

33. 33 Example Dashboard

34. 34 Clicking on Virginia drills down to Inventory by City AlexandriaRichmondRoanoke Inventory Level

35. 35 Data Mining Knowledge Discovery Identify patterns in your data

36. 36 Market Basket Analysis Identify items purchased together

37. 37 Data Mining Tasks Predict –Churn Analysis –Increase response rate Estimate –Customer satisfaction and renewal rate Classify –Fraud Detection

38. 38 Business Intelligence Tools

39. 39 Enterprise Architecture Production Systems ExtractLoad Transform Data Warehouse ReportingOLAPGUI Data Mining External Data Sources

40. 40 Open Source Technologies ExtractLoadTransform Data Warehouse Data Mining Reporting JasperSoft Reporting Warehouse MySQL Mining Weka Pentaho Data Integration (ETL)

41. 41

42. 42 Service Providers Software as a Service (SaaS) On Demand Hosted Applications

43. 43 Attaain Inc. Active Intelligence for Strategic Advantage ™ Competitive Intelligence Real-time intelligence  Companies, people and markets Easy to use, web-based system Customized tracking according to your company’s lines of business Online dashboard Automated e-mail alerts Extensive web marketing analytics Cost-effective month-to-month subscription

44. 44 RU Can Help You Six Concentrations Internships and Permanent positions Small Project Support Center Computer ScienceInformation SystemsDatabase Software EngineeringNetworkingWeb Development

45. 45 References Attaain JasperSoft MySQL Pentaho Weka

46. 46 References Attaainhttp://www.attaain.com/ JasperSofthttp://www.jaspersoft.com/ MySQLhttp://www.mysql.com/ Pentahohttp://www.pentaho.com/ Weka http://www.cs.waikato.ac.nz/ml/ weka/