1. 1 McGraw-Hill/Irwin Copyright © 2004, The McGraw-Hill Companies, Inc. All rights reserved. Chapter 3 Data Resource Management

2. 2 McGraw-Hill/Irwin Copyright © 2004, The McGraw-Hill Companies, Inc. All rights reserved. Learning Objectives  Explain the importance of implementing data resource management processes and technologies in an organization.  Understand the advantages of a database management approach to managing the data resources of a business.

3. 3 McGraw-Hill/Irwin Copyright © 2004, The McGraw-Hill Companies, Inc. All rights reserved. Learning Objectives (continued)  Explain how database management software helps business professionals and supports the operations and management of a business.  Illustrate each of the following concepts:  Major types of databases  Data warehouses and data mining  Logical data elements  Fundamental database structures  Database access methods  Database development

4. 4 McGraw-Hill/Irwin Copyright © 2004, The McGraw-Hill Companies, Inc. All rights reserved. Section I Managing Data Resources

5. 5 McGraw-Hill/Irwin Copyright © 2004, The McGraw-Hill Companies, Inc. All rights reserved. Data Resource Management  A managerial activity  Applies information systems technology to managing data resources to meet needs of business stakeholders.

6. 6 McGraw-Hill/Irwin Copyright © 2004, The McGraw-Hill Companies, Inc. All rights reserved. Foundation Data Concepts  Levels of data  Character  Single alphabetical, numeric, or other symbol  Field  Groupings of characters  Represents an attribute of some entity

7. 7 McGraw-Hill/Irwin Copyright © 2004, The McGraw-Hill Companies, Inc. All rights reserved. Foundation Data Concepts (continued)  Records  Related fields of data  Collection of attributes that describe an entity  Fixed-length or variable-length

8. 8 McGraw-Hill/Irwin Copyright © 2004, The McGraw-Hill Companies, Inc. All rights reserved. Foundation Data Concepts (continued)  Files (table)  A group of related records  Classified by  Primary use  Type of data  permanence

9. 9 McGraw-Hill/Irwin Copyright © 2004, The McGraw-Hill Companies, Inc. All rights reserved. Foundation Data Concepts (continued)  Database  Integrated collection of logically related data elements  Consolidates records into a common pool of data elements  Data is independent of the application program using them and type of storage device

10. 10 McGraw-Hill/Irwin Copyright © 2004, The McGraw-Hill Companies, Inc. All rights reserved. Foundation Data Concepts (continued)  Logical Data Elements

11. 11 McGraw-Hill/Irwin Copyright © 2004, The McGraw-Hill Companies, Inc. All rights reserved. Types of Databases  Operational  Supports business processes and operations  Also called subject-area databases, transaction databases, and production databases

12. 12 McGraw-Hill/Irwin Copyright © 2004, The McGraw-Hill Companies, Inc. All rights reserved. Types of Databases (continued)  Distributed  Replicated and distributed copies or parts of databases on network servers at a variety of sites.  Done to improve database performance and security

13. 13 McGraw-Hill/Irwin Copyright © 2004, The McGraw-Hill Companies, Inc. All rights reserved. Types of Databases (continued)  External  Available for a fee from commercial sources or with or without charge on the Internet or World Wide Web  Hypermedia  Hyperlinked pages of multimedia

14. 14 McGraw-Hill/Irwin Copyright © 2004, The McGraw-Hill Companies, Inc. All rights reserved. Data Warehouses and Data Mining  Data warehouse  Stores data extracted from operational, external, or other databases of an organization  Central source of “structured” data  May be subdivided into data marts

15. 15 McGraw-Hill/Irwin Copyright © 2004, The McGraw-Hill Companies, Inc. All rights reserved. Data Warehouses and Data Mining (continued)  Data mining  A major use of data warehouse databases  Data is analyzed to reveal hidden correlations, patterns, and trends

16. 16 McGraw-Hill/Irwin Copyright © 2004, The McGraw-Hill Companies, Inc. All rights reserved. Database Management Approach  Consolidates data records and objects into databases that can be accessed by many different application programs

17. 17 McGraw-Hill/Irwin Copyright © 2004, The McGraw-Hill Companies, Inc. All rights reserved. Database Management Approach (continued)  Database Management System  Software interface between users and databases  Controls creation, maintenance, and use of the database

18. 18 McGraw-Hill/Irwin Copyright © 2004, The McGraw-Hill Companies, Inc. All rights reserved. Database Management Approach (continued)

19. 19 McGraw-Hill/Irwin Copyright © 2004, The McGraw-Hill Companies, Inc. All rights reserved. Database Management Approach (continued)  Database Interrogation  Query  Supports ad hoc requests  Tells the software how you want to organize the data  SQL queries  Graphical (GUI) & natural queries

20. 20 McGraw-Hill/Irwin Copyright © 2004, The McGraw-Hill Companies, Inc. All rights reserved. Database Management Approach (continued)  Report Generator  Turns results of query into a useable report  Database Maintenance  Updating and correcting data

21. 21 McGraw-Hill/Irwin Copyright © 2004, The McGraw-Hill Companies, Inc. All rights reserved. Database Management Approach (continued)  Application Development  Data manipulation language  Data entry screens, forms, reports, or web pages

22. 22 McGraw-Hill/Irwin Copyright © 2004, The McGraw-Hill Companies, Inc. All rights reserved. Implementing Data Resource Management  Database Administration  Develop and maintain the data dictionary  Design and monitor performance of databases  Enforce database use and security standards

23. 23 McGraw-Hill/Irwin Copyright © 2004, The McGraw-Hill Companies, Inc. All rights reserved. Implementing Data Resource Management (continued)  Data Planning  Corporate planning and analysis function  Developing the overall data architecture

24. 24 McGraw-Hill/Irwin Copyright © 2004, The McGraw-Hill Companies, Inc. All rights reserved. Implementing Data Resource Management (continued)  Data Administration  Standardize collection, storage, and dissemination of data to end users  Focused on supporting business processes and strategic business objectives  May include developing policy and setting standards

25. 25 McGraw-Hill/Irwin Copyright © 2004, The McGraw-Hill Companies, Inc. All rights reserved. Implementing Data Resource Management (continued)  Challenges  Technologically complex  Vast amounts of data  Vulnerability to fraud, errors, and failures

26. 26 McGraw-Hill/Irwin Copyright © 2004, The McGraw-Hill Companies, Inc. All rights reserved. Section II Technical Foundations of Database Management

27. 27 McGraw-Hill/Irwin Copyright © 2004, The McGraw-Hill Companies, Inc. All rights reserved. Database Structures  Hierarchical  Treelike  One-to-many relationship  Used for structured, routine types of transaction processing

28. 28 McGraw-Hill/Irwin Copyright © 2004, The McGraw-Hill Companies, Inc. All rights reserved. Database Structures (continued)  Network  More complex  Many-to-many relationship  More flexible but doesn’t support ad hoc requests well

29. 29 McGraw-Hill/Irwin Copyright © 2004, The McGraw-Hill Companies, Inc. All rights reserved. Database Structures (continued)  Relational  Data elements stored in simple tables  Can link data elements from various tables  Very supportive of ad hoc requests but slower at processing large amounts of data than hierarchical or network models

30. 30 McGraw-Hill/Irwin Copyright © 2004, The McGraw-Hill Companies, Inc. All rights reserved. Database Structures (continued)  Multi-Dimensional  A variation of the relational model  Cubes of data and cubes within cubes  Popular for online analytical processing (OLAP) applications

31. 31 McGraw-Hill/Irwin Copyright © 2004, The McGraw-Hill Companies, Inc. All rights reserved. Database Structures (continued)

32. 32 McGraw-Hill/Irwin Copyright © 2004, The McGraw-Hill Companies, Inc. All rights reserved. Database Structures (continued)  Object-oriented  Key technology of multimedia web-based applications  Good for complex, high-volume applications

33. 33 McGraw-Hill/Irwin Copyright © 2004, The McGraw-Hill Companies, Inc. All rights reserved. Database Structures (continued)

34. 34 McGraw-Hill/Irwin Copyright © 2004, The McGraw-Hill Companies, Inc. All rights reserved. Accessing Databases  Key fields (primary key)  A field unique to each record so it can be distinguished from all other records in a table

35. 35 McGraw-Hill/Irwin Copyright © 2004, The McGraw-Hill Companies, Inc. All rights reserved. Accessing Databases (continued)  Sequential access  Data is stored and accessed in a sequence according to a key field  Good for periodic processing of a large volume of data, but updating with new transactions can be troublesome

36. 36 McGraw-Hill/Irwin Copyright © 2004, The McGraw-Hill Companies, Inc. All rights reserved. Accessing Databases (continued)  Direct access  Methods  Key transformation  Index  Indexed sequential access

37. 37 McGraw-Hill/Irwin Copyright © 2004, The McGraw-Hill Companies, Inc. All rights reserved. Database Development  Data dictionary  Directory containing metadata (data about data)  Structure  Data elements  Interrelationships  Information regarding access and use  Maintenance & security issues

38. 38 McGraw-Hill/Irwin Copyright © 2004, The McGraw-Hill Companies, Inc. All rights reserved. Database Development (continued)  Data Planning & Database Design  Planning & Design Process  Enterprise model  Entity relationship diagrams (ERDs)  Data modeling  Develop logical framework for the physical design

39. 39 McGraw-Hill/Irwin Copyright © 2004, The McGraw-Hill Companies, Inc. All rights reserved. Discussion Questions  How should an e-business enterprise store, access, and distribute data & information about their internal operations & external environment?  What roles do database management, data administration, and data planning play in managing data as a business resource?

40. 40 McGraw-Hill/Irwin Copyright © 2004, The McGraw-Hill Companies, Inc. All rights reserved. Discussion Questions (continued)  What are the advantages of a database management approach to organizing, accessing, and managing an organization’s data resources?  What is the role of a database management system in an e-business information system?

41. 41 McGraw-Hill/Irwin Copyright © 2004, The McGraw-Hill Companies, Inc. All rights reserved. Discussion Questions (continued)  Databases of information about a firm’s internal operations were formerly the only databases that were considered to be important to a business. What other kinds of databases are important for a business today?  What are the benefits and limitations of the relational database model for business applications?

42. 42 McGraw-Hill/Irwin Copyright © 2004, The McGraw-Hill Companies, Inc. All rights reserved. Discussion Questions (continued)  Why is the object-oriented database model gaining acceptance for developing applications and managing the hypermedia databases at business websites?  How have the Internet, intranets, extranets, and the World Wide Web affected the types and uses of data resources available to business end users?

43. 43 McGraw-Hill/Irwin Copyright © 2004, The McGraw-Hill Companies, Inc. All rights reserved. Real World Case 1 – IBM versus Oracle  What key business strategies did Janet Perna implement to help IBM catch up to Oracle in the database management software market?  What is the business case for both IBM’s and Oracle’s product strategy for their database software?

44. 44 McGraw-Hill/Irwin Copyright © 2004, The McGraw-Hill Companies, Inc. All rights reserved. Real World Case 1 (continued)  Which approach would you recommend to a company seeking a database system today?  What do you see as the key factor to IBM’s success?

45. 45 McGraw-Hill/Irwin Copyright © 2004, The McGraw-Hill Companies, Inc. All rights reserved. Real World Case 1 (continued)  The case states that “database software has become more of a commodity.” Do you agree?

46. 46 McGraw-Hill/Irwin Copyright © 2004, The McGraw-Hill Companies, Inc. All rights reserved. Real World Case 2 – Experian Automotive  How do the database software tools discussed in this case help companies exploit their data resources?  What is the business value of the automotive database created by Experian?

47. 47 McGraw-Hill/Irwin Copyright © 2004, The McGraw-Hill Companies, Inc. All rights reserved. Real World Case 2 (continued)  What other business opportunities could you recommend to Experian that would capitalize on their automotive database?  The case states that Experian’s automotive database “has raised the hackles of privacy advocates.” What legitimate privacy concerns and safeguard suggestions might be raised about this database and its use?

48. 48 McGraw-Hill/Irwin Copyright © 2004, The McGraw-Hill Companies, Inc. All rights reserved. Real World Case 3 – Shell Exploration  Why do companies still have problems with the quality of the data resources stored in their business information systems?  What is a “data silo?”

49. 49 McGraw-Hill/Irwin Copyright © 2004, The McGraw-Hill Companies, Inc. All rights reserved. Real World Case 3 (continued)  How do data warehouse approaches help companies like Shell and OshKosh meet their data resource management challenges?  What business benefits can companies derive from a data warehouse approach?

50. 50 McGraw-Hill/Irwin Copyright © 2004, The McGraw-Hill Companies, Inc. All rights reserved. Real World Case 4 – BlueCross BlueShield & Warner Bros.  What is a storage area network? Why are so many companies installing SANs?  What are the reasons for the quick payback on SAN investments?

51. 51 McGraw-Hill/Irwin Copyright © 2004, The McGraw-Hill Companies, Inc. All rights reserved. Real World Case 4 (continued)  What are the challenges and alternatives to SANs as a data storage technology?  What are some advantages of SANs?

52. 52 McGraw-Hill/Irwin Copyright © 2004, The McGraw-Hill Companies, Inc. All rights reserved. Real World Case 5 – Sherwin-Williams & Krispy Kreme  Tips for Managing External Data  Purchase external data from a reliable source that will do most of the refining for you and will work with you on contingency plans.  Run a test load first. A load of test data can pave the way for accurate production loads.

53. 53 McGraw-Hill/Irwin Copyright © 2004, The McGraw-Hill Companies, Inc. All rights reserved. Real World Case 5 (continued)  Managing external data (continued)  Don’t collect data until business and IT staff have agreed on the amount, frequency, format, and content of the data you need.  Don’t acquire more data or use more data sources than you really need.

54. 54 McGraw-Hill/Irwin Copyright © 2004, The McGraw-Hill Companies, Inc. All rights reserved. Real World Case 5 (continued)  Managing external data (continued)  Don’t mingle external and homegrown data without adding unique identifiers to each record, in case you need to pull it out.  Don’t overestimate the data’s integrity. Nothing beats direct customer contact and tactical details behind the data.

55. 55 McGraw-Hill/Irwin Copyright © 2004, The McGraw-Hill Companies, Inc. All rights reserved. Real World Case 5 (continued)  What challenges in acquiring and using data from external sources are identified in this case?  Do you prefer the Sherwin-Williams or Krispy Kreme approach to acquiring external data?

56. 56 McGraw-Hill/Irwin Copyright © 2004, The McGraw-Hill Companies, Inc. All rights reserved. Real World Case 5 (continued)  What other sources of external data might a business use to gain valuable marketing and competitive intelligence?