1. McGraw-Hill/Irwin ©2005 The McGraw-Hill Companies, All rights reserved ©2005 The McGraw-Hill Companies, All rights reserved McGraw-Hill/Irwin

2. McGraw-Hill/Irwin ©2005 The McGraw-Hill Companies, All rights reserved CHAPTER 3 DATABASES AND DATA WAREHOUSES

3. 3-3 OPENING CASE STUDY Chrysler Spins a Competitive Advantage with Supply Chain Management Software Chapter 2 – supply chain management is a key business initiative Chrysler’s SCM is called SPIN, a Web-based system

4. 3-4 OPENING CASE STUDY Behind SPIN are powerful databases Databases store a wealth of information –Inventory –Work-in-progress –Supplier information –Recall notices –Customer purchases This chapter – databases and data warehouses

5. 3-5 STUDENT LEARNING OUTCOMES 1.Describe business intelligence and its role 2.Compare databases and data warehouses by OLTP and OLAP 3.List/describe key characteristics of a relational database 4.Define 5 software components of a DBMS

6. 3-6 STUDENT LEARNING OUTCOMES 5.List/describe key characteristics of a data warehouse 6.Define 4 major types of data-mining tools 7.List key considerations in managing information as a resource

7. 3-7 INTRODUCTION Organizations need business intelligence Business intelligence (BI) – knowledge about your customers, competitors, business partners, competitive environment, and internal operations to make effective, important, and strategic business decisions

8. 3-8 INTRODUCTION IT tools help process information to create business intelligence according to: –OLTP –OLAP

9. 3-9 INTRODUCTION Online transaction processing (OLTP) – the gathering of input information, processing that information, and updating existing information to reflect the gathered and processed information –Databases support OLTP –Operational database – databases that support OLTP

10. 3-10 INTRODUCTION Online analytical processing (OLAP) – the manipulation of information to support decision making –Databases can support some OLAP –Data warehouses only support OLAP, not OLTP –Data warehouses are special forms of databases that support decision making

11. 3-11 INTRODUCTION

12. 3-12 THE RELATIONAL DATABASE MODEL There are many types of databases The relational database model is the most popular Relational database – uses a series of logically related two-dimensional tables or files to store information in the form of a database

13. 3-13 Databases Are… Collections of information Created with logical structures With logical ties within the information With built-in integrity constraints

14. 3-14 Databases – Collections of Information Databases have many tables Consider Solomon Enterprises that provides concrete to home and commercial builders. Tables or files include: –Order –Customer –Concrete Type –Employee –Truck

15. 3-15 Databases – Collections of Information

16. 3-16 Databases – Created with Logical Structures In databases, the row number is irrelevant Not true in spreadsheet software In databases, column names are very important. Column names are created in the data dictionary Data dictionary – contains the logical structure of the information in a database

17. 3-17 Databases – With Logical Ties Within the Information Logical ties must exist between the tables or files in a database Logical ties are created with primary and foreign keys Primary key – field (or group of fields in some cases) that uniquely describes each record Can you find primary keys in Figure 3.1 on page 129?

18. 3-18 Databases – With Logical Ties Within the Information Foreign key – primary key of one file that appears in another file Foreign keys help you create logical ties within the information in a database

19. 3-19 Databases – With Logical Ties Within the Information

20. 3-20 Databases – With Built-In Integrity Constraints Integrity constraints – rules that help ensure the quality of the information Examples –Primary keys must be unique –Foreign keys must be present –Sales price cannot be negative –Phone number must have area code

21. 3-21 DATABASE MANAGEMENT SYSTEM TOOLS Database management system (DBMS) – helps you specify the logical organization for a databases and access and use the information within a database –Word processing software = document –Spreadsheet software = workbook –DBMS software = database

22. 3-22 DATABASE MANAGEMENT SYSTEM TOOLS 5 software components: 1.DBMS engine 2.Data definition subsystem 3.Data manipulation subsystem 4.Application generation subsystem 5.Data administration subsystem

23. 3-23 DATABASE MANAGEMENT SYSTEM TOOLS

24. 3-24 DBMS Engine DBMS engine – accepts logical requests from the various other DBMS subsystems, converts them into their physical equivalent, and actually accesses the database and data dictionary as they exist on a storage device DBMS engine separates the logical from the physical

25. 3-25 DBMS Engine Physical view – how information is physically arranged, stored, and accessed on some type of storage device Logical view – how you as a knowledge worker need to arrange and access information With a database, you only concern yourself with your logical view

26. 3-26 Data Definition Subsystem Data definition subsystem – helps you create and maintain the data dictionary and define the structure of the files in a database You must create a data dictionary before entering information into a database Module J covers this for Microsoft Access

27. 3-27 Data Manipulation Subsystem Data manipulation subsystem – helps you add, change, and delete information This is your primary DBMS interface as you work with a database –Views –Report generators –QBE tools –SQL

28. 3-28 Views View – allows you to see the contents of a database file –Make whatever changes you want –Perform simple sorting –Query to find the location of information –Looks similar to a workbook with no row numbers

29. 3-29 Views

30. 3-30 Report Generators Report generator – helps you quickly define formats of reports and what information you want to see in a report You can save report formats and generate reports at any time with up-to-date information

31. 3-31 Report Generators

32. 3-32 Report Generators

33. 3-33 QBE Tools Query-by-example (QBE) tool – helps you graphically design the answer to a question “What driver most often delivers concrete to Triple A Homes?”

34. 3-34 QBE Tools

35. 3-35 SQL Structured query language (SQL) – standardized fourth-generation language found in most DBMSs Performs the same task as a QBE tool –But uses a sentence structure instead of point- and-click interface SQL is used mostly by IT people

36. 3-36 Application Generation Subsystem Application generation subsystem – contains facilities to help you develop transaction-intensive applications –Data entry screen (called forms) –Programming languages Used mostly by IT specialists

37. 3-37 Data Administration Subsystem Data administration subsystem – helps you manage the overall database environment –Backup and recovery –Security management –Query optimization –Concurrency control –Change management

38. 3-38 Data Administration Subsystem Backup and recovery –Periodically back up information –Recover a database if a failure occurs Security management –Who has access to what information –Who can perform certain tasks (e.g., add, change, or delete) on information

39. 3-39 Data Administration Subsystem Query optimization –Restructure physical view of information to optimize response times to queries Concurrency control –What happens if two people makes changes to the same information at the same time?

40. 3-40 Data Administration Subsystem Change management –What is the effect of structural changes to a database? –What if you add a new column? –What happens if you delete a column? –What happens if you change a column’s attributes?

41. 3-41 DATA WAREHOUSES AND DATA MINING Data warehouses support OLAP and decision making Data warehouses do not support OLTP Data-mining tools are the tools you use to work with a data warehouse –DBMS software = database –Data-mining tools = data warehouse

42. 3-42 What Is a Data Warehouse? Data warehouse – logical collection of information – gathered from operational databases – used to create business intelligence that supports business analysis activities and decision-making tasks

43. 3-43 What Is a Data Warehouse?

44. 3-44 What Is a Data Warehouse? Multidimensional Rows and columns Also layers Many times called hypercubes What are the dimensions in Figure 3.8 on page 142?

45. 3-45 What Are Data-Mining Tools? Data-mining tools – software tools that you use to query information in a data warehouse –Query-and-reporting tools –Intelligence agents –Multidimensional analysis tools –Statistical tools

46. 3-46 What Are Data-Mining Tools?

47. 3-47 Query-And-Reporting Tools Query-and-reporting tools – similar to QBE tools, SQL, and report generators in the typical database environment

48. 3-48 Intelligent Agents Use various artificial intelligence tools such as neural networks and fuzzy logic to form the basis for “information discovery” and building business intelligence Help you find hidden patterns in information Chapter 4 focuses more on these

49. 3-49 Multidimensional Analysis Tools Multidimensional analysis (MDA) tools – slice-and-dice techniques that allow you to view multidimensional information from different perspectives –Bring new layers to the front –Reorganize rows and columns

50. 3-50 Statistical Tools Help you apply various mathematical models to the information stored in a data warehouse to discover new information –Regression –Analysis of variance –And so on

51. 3-51 Data Marts Data warehouses can support all of an organization’s information Data marts have subsets of an organizationwide data warehouse Data mart – subset of a data warehouse in which only a focused portion of the data warehouse information is kept

52. 3-52 Data Marts

53. 3-53 Data Mining as a Career Opportunity Knowledge of data mining can be a substantial career opportunity for you –Query and Analysis and Enterprise Analytic Tools (Business Objects) –Business Intelligence and Information Access tools (SAS) –Many in Cognos (the data warehouse leader) –PowerAnalyzer (Informatica)

54. 3-54 Considerations in Using a Data Warehouse Do you need a data warehouse? –Perhaps database OLAP is sufficient Do all employees need the entire data warehouse? –If no, build smaller data marts How up-to-date must the information be? What data-mining tools do you need?

55. 3-55 MANAGING THE INFORMATION RESOURCE Information is an organizational resource Just like people, capital, and equipment It must be managed effectively

56. 3-56 MANAGING THE INFORMATION RESOURCE Who should oversee your organization’s information resource? –Chief information officer (CIO) – oversees an organization’s information resource –Data administration – plans for, oversees the development of, and monitors the information resource –Database administration – technical and operational aspects of managing information

57. 3-57 MANAGING THE INFORMATION RESOURCE Is information ownership a consideration? –If you create information, you “own” it –You will also share it with others –Because you “own” it, you are responsible for its quality

58. 3-58 MANAGING THE INFORMATION RESOURCE How “clean” must your information be? –Duplicate information (records) must be eliminated –Inaccurate information must be corrected –Information forms the basis of business intelligence –If your business intelligence is bad, you will make poor decisions

59. 3-59 CAN YOU… 1.Describe business intelligence and its role 2.Compare databases and data warehouses by OLTP and OLAP 3.List/describe key characteristics of a relational database 4.Define 5 software components of a DBMS

60. 3-60 CAN YOU… 5.List/describe key characteristics of a data warehouse 6.Define 4 major types of data-mining tools 7.List key considerations in managing information as a resource

61. McGraw-Hill/Irwin ©2005 The McGraw-Hill Companies, All rights reserved CHAPTER 3 End of Chapter 3