Chapter 3 DATABASES AND DATA WAREHOUSES Building Business Intelligence

1. Chapter 3DATABASES AND DATA WAREHOUSESBuilding Business Intelligence

2. STUDENT LEARNING OUTCOMES

3. CAN COMPANIES KEEP YOUR PERSONAL INFORMATION PRIVATE AND SECURE?

4. Big Information Loss Examples

5. Questions Have you been a victim of identity theft? If so, what happened? What can you do to protect yourself from identity theft? How many organizations have your credit card number?

6. INTRODUCTION Businesses use many IT tools to manage and organize information for many reasons Online transaction processing (OLTP) Online analytical processing (OLAP)

7. INTRODUCTION • OLTP • OLAP

8. OLTP, OLAP, and Business Intelligence

9. CHAPTER ORGANIZATION • Relational Database Model • Database Management System Tools • Data Warehouses and Data Mining • Business Intelligence Revisited • Information Ownership

10. RELATIONAL DATABASE MODEL • Database • Relational database

11. Database Characteristics

12. Database – Collection of Information

13. Database – Created with Logical Structures Before you can enter information into a database, you must define the data dictionary for all the tables and their fields. For example, when you create the Truck table, you must specify that it will have three pieces of information and that Date of Purchase is a field in Date format. Data dictionary

14. Database – Logical Ties within the Information Customer Number is the primary key for Customer and appears in Order as a foreign key Primary key Foreign key

15. Database – Logical Ties within the Information

16. Databases – Built-In Integrity Constraints Integrity constraints Data dictionary Foreign keys

17. DATABASE MANAGEMENT SYSTEM TOOLS Database management system (DBMS)

18. 5 Components of a DBMS

19. DBMS Engine • DBMS engine • Physical view • Logical view

20. Data Definition Subsystem Data definition subsystem The data dictionary helps you define…

21. Data Manipulation Subsystem Data manipulation subsystem Includes views, report generators, query-by-example tools, and structured query language

22. View Binoculars • View

23. Report Generator Report generator

24. Query-by-Example Tool QBE tool

25. Structured Query Language SQL

26. Application Generation Subsystem Application generation subsystem

27. Data Administration Subsystem Data administration subsystem

28. Data Administration Subsystem • Backup and recovery • Backup • Recovery

29. Data Administration Subsystem Security management Query optimization Reorganization

30. Data Administration Subsystem • Concurrency control • Change management

31. DATA WAREHOUSES AND DATA MINING Help you build and work with business intelligence and some forms of knowledge Data warehouse

32. Data Warehouse Characteristics • Multidimensional • Support decision making, not transaction processing

33. Data-Mining Tools Data-mining tools

34. Data-Mining Tools Query-and-reporting tools Intelligent agents Multidimensional analysis (MDA tools) Statistical tools

35. Data Marts • Data mart

36. Data Warehouse Considerations

37. BUSINESS INTELLIGENCE REVISITED • Business intelligence (BI) • Hot topic in business today • Current market is $50 billion and double-digit annual growth

38. BI Objectives Help people understand several things:

39. Building Business Intelligence

40. Viewing Business Intelligence Digital dashboard

41. INFORMATION OWNERSHIP Information is a resource you must manage and organize to help the organization meet its goals and objectives You need to consider several things:

42. Strategic Management Support Covered many c-level positions in Chapter 2 for IT 2 others in information management Data administration Database administration

43. Sharing Information Everyone can share – while not consuming – information But someone must “own” it by accepting responsibility for its quality and accuracy

44. Information Cleanliness