1. CHAPTER 1: THE DATABASE ENVIRONMENT AND DEVELOPMENT PROCESS Modern Database Management 11 th Edition Jeffrey A. Hoffer, V. Ramesh, Heikki Topi © 2013 Pearson Education, Inc. Publishing as Prentice Hall 1

2. Chapter 1 © 2013 Pearson Education, Inc. Publishing as Prentice Hall  Salaries and current jobs available for database professionals www.payscale.comwww.payscale.com  Database Analyst (39,512 – 88,354) Median – 56,884 Database Analyst  This is non-specific; I just gathered the average, high and low for this job title. Feel free to go to the site, put in more detailed information, and see what’s available.

3. Chapter 1 © 2013 Pearson Education, Inc. Publishing as Prentice Hall  Your ability to manage stuff (things, people, customer relationships, etc…) is dependent on your ability to keep track of data about it  Your ability to keep track of data is dependent on your ability to find it  Your ability to find your data is dependent on how well you store it

4. Chapter 1 © 2013 Pearson Education, Inc. Publishing as Prentice Hall  Define terms  Name limitations of conventional file processing  Explain advantages of databases  Identify costs and risks of databases  List components of database environment  Identify categories of database applications  Describe database system development life cycle  Explain prototyping and agile development approaches  Explain roles of individuals  Explain the three-schema architecture for databases 4

5. Chapter 1 © 2013 Pearson Education, Inc. Publishing as Prentice Hall DEFINITIONS  Database: organized collection of logically related data  Data: stored representations of meaningful objects and events  Structured: numbers, text, dates  Unstructured: images, video, documents  Information: data processed to increase knowledge in the person using the data  Metadata: data that describes the properties and context of user data 5

6. 6 Figure 1-1a Data in context Context helps users understand data 6 Chapter 1 © 2013 Pearson Education, Inc. Publishing as Prentice Hall

7. 7 Graphical displays turn data into useful information that managers can use for decision making and interpretation Figure 1-1b Summarized data 7 Chapter 1 © 2013 Pearson Education, Inc. Publishing as Prentice Hall

8. 8 Descriptions of the properties or characteristics of the data, including data types, field sizes, allowable values, and data context 8 Chapter 1 © 2013 Pearson Education, Inc. Publishing as Prentice Hall

9. Chapter 1 © 2013 Pearson Education, Inc. Publishing as Prentice Hall DISADVANTAGES OF FILE PROCESSING  Program-Data Dependence  All programs maintain metadata for each file they use  Duplication of Data  Different systems/programs have separate copies of the same data  Limited Data Sharing  No centralized control of data  Lengthy Development Times  Programmers must design their own file formats  Excessive Program Maintenance  80% of information systems budget 9

10. Chapter 1 © 2013 Pearson Education, Inc. Publishing as Prentice Hall PROBLEMS WITH DATA DEPENDENCY  Each application programmer must maintain his/her own data  Each application program needs to include code for the metadata of each file  Each application program must have its own processing routines for reading, inserting, updating, and deleting data  Lack of coordination and central control  Non-standard file formats 10

11. Chapter 1 © 2013 Pearson Education, Inc. Publishing as Prentice Hall Data Program 1 Program 2 Program 3 Meta-Data Traditional File System Database Management System Data Meta-Data Data Meta-Data Program 2 Program 3 Program 1

12. 12 Duplicate Data 12 Chapter 1 © 2013 Pearson Education, Inc. Publishing as Prentice Hall

13. Chapter 1 © 2013 Pearson Education, Inc. Publishing as Prentice Hall PROBLEMS WITH DATA REDUNDANCY  Waste of space to have duplicate data  Causes more maintenance headaches  The biggest problem:  Data changes in one file could cause inconsistencies  Compromises in data integrity 13

14. Chapter 1 © 2013 Pearson Education, Inc. Publishing as Prentice Hall SOLUTION: THE DATABASE APPROACH  Central repository of shared data  Data is managed by a controlling agent  Stored in a standardized, convenient form 14 Requires a Database Management System (DBMS)

15. Chapter 1 © 2013 Pearson Education, Inc. Publishing as Prentice Hall DATABASE MANAGEMENT SYSTEM 15 DBMS manages data resources like an operating system manages hardware resources A software system that is used to create, maintain, and provide controlled access to user databases Order Filing System Invoicing System Payroll System DBMS Central database Contains employee, order, inventory, pricing, and customer data

16. Chapter 1 © 2013 Pearson Education, Inc. Publishing as Prentice Hall ADVANTAGES OF THE DATABASE APPROACH  Program-data independence  Planned data redundancy  Improved data consistency  Improved data sharing  Increased application development productivity  Enforcement of standards  Improved data quality  Improved data accessibility and responsiveness  Reduced program maintenance  Improved decision support 16

17. Chapter 1 © 2013 Pearson Education, Inc. Publishing as Prentice Hall  New, specialized personnel  Installation and management cost and complexity  Conversion costs  Need for explicit backup and recovery  Organizational conflict 17

18. Chapter 1 © 2013 Pearson Education, Inc. Publishing as Prentice Hall  Data models  Graphical system capturing nature and relationship of data  Enterprise Data Model–high-level entities and relationships for the organization  Project Data Model–more detailed view, matching data structure in database or data warehouse  Entities  Noun form describing a person, place, object, event, or concept  Composed of attributes  Relationships  Between entities  Usually one-to-many (1:M) or many-to-many (M:N)  Relational Databases  Database technology involving tables (relations) representing entities and primary/foreign keys representing relationships 18

19. 19 Segment of an enterprise data model Segment of a project-level data model Figure 1-3 Comparison of enterprise and project level data models 19 Chapter 1 © 2013 Pearson Education, Inc. Publishing as Prentice Hall

20. 20 One customer may place many orders, but each order is placed by a single customer  One-to-many relationship 20 Chapter 1 © 2013 Pearson Education, Inc. Publishing as Prentice Hall

21. 21 One order has many order lines; each order line is associated with a single order  One-to-many relationship 21 Chapter 1 © 2013 Pearson Education, Inc. Publishing as Prentice Hall

22. 22 One product can be in many order lines, each order line refers to a single product  One-to-many relationship 22 Chapter 1 © 2013 Pearson Education, Inc. Publishing as Prentice Hall

23. 23 Therefore, one order involves many products and one product is involved in many orders  Many-to-many relationship 23 Chapter 1 © 2013 Pearson Education, Inc. Publishing as Prentice Hall

24. Chapter 1 © 2013 Pearson Education, Inc. Publishing as Prentice Hall Relationships established in special columns that provide links between tables

25. 25 Chapter 1 © 2013 Pearson Education, Inc. Publishing as Prentice Hall

26. Chapter 1 © 2013 Pearson Education, Inc. Publishing as Prentice Hall 26 Figure 1-5 Components of the Database Environment

27. Chapter 1 © 2013 Pearson Education, Inc. Publishing as Prentice Hall  Create new records (inserting new data)  Read data for display  Updating existing data  Deleting existing data

28. Chapter 1 © 2013 Pearson Education, Inc. Publishing as Prentice Hall  CASE Tools–computer-aided software engineering  Repository–centralized storehouse of metadata  Database Management System (DBMS) –software for managing the database  Database–storehouse of the data  Application Programs–software using the data  User Interface–text and graphical displays to users  Data/Database Administrators–personnel responsible for maintaining the database  System Developers–personnel responsible for designing databases and software  End Users–people who use the applications and databases 28

29. Chapter 1 © 2013 Pearson Education, Inc. Publishing as Prentice Hall  most formal development methodologies are documentation based  helps managers monitor progress and quality of project  facilitates communication between team members  includes models  various stages are not complete until documentation is accepted

30. Chapter 1 © 2013 Pearson Education, Inc. Publishing as Prentice Hall  accurate requirements definition  commitment  effective change management  manageable size  champion

31. 31 FIGURE 1-6 Example business function-to-data entity matrix 31 Chapter 1 © 2013 Pearson Education, Inc. Publishing as Prentice Hall

32. Chapter 1 © 2013 Pearson Education, Inc. Publishing as Prentice Hall  SDLC  System Development Life Cycle  Detailed, well-planned development process  Time-consuming, but comprehensive  Long development cycle  Prototyping  Rapid application development (RAD)  Cursory attempt at conceptual data modeling  Define database during development of initial prototype  Repeat implementation and maintenance activities with new prototype versions 32

33. Chapter 1 © 2013 Pearson Education, Inc. Publishing as Prentice Hall SYSTEMS DEVELOPMENT LIFE CYCLE (SEE ALSO FIGURE 1-7) 33 Planning Analysis Physical Design Implementation Maintenance Logical Design

34. Chapter 1 © 2013 Pearson Education, Inc. Publishing as Prentice Hall SYSTEMS DEVELOPMENT LIFE CYCLE (SEE ALSO FIGURE 1-7) (CONT.) 34 Planning Analysis Physical Design Implementation Maintenance Logical Design Planning – Purpose – preliminary understanding – Deliverable – request for study – Database activity – enterprise modeling and early conceptual data modeling

35. Chapter 1 © 2013 Pearson Education, Inc. Publishing as Prentice Hall SYSTEMS DEVELOPMENT LIFE CYCLE (SEE ALSO FIGURE 1-7) (CONT.) 35 Planning Analysis Physical Design Implementation Maintenance Logical Design Analysis Purpose–thorough requirements analysis and structuring Deliverable–functional system specifications Database activity–thorough and integrated conceptual data modeling

36. Chapter 1 © 2013 Pearson Education, Inc. Publishing as Prentice Hall SYSTEMS DEVELOPMENT LIFE CYCLE (SEE ALSO FIGURE 1-7) (CONT.) 36 Planning Analysis Physical Design Implementation Maintenance Logical Design Purpose–information requirements elicitation and structure Deliverable–detailed design specifications Database activity– logical database design (transactions, forms, displays, views, data integrity and security)

37. Chapter 1 © 2013 Pearson Education, Inc. Publishing as Prentice Hall SYSTEMS DEVELOPMENT LIFE CYCLE (SEE ALSO FIGURE 1-7) (CONT.) 37 Planning Analysis Physical Design Implementation Maintenance Logical Design Physical Design Purpose–develop technology and organizational specifications Deliverable–program/data structures, technology purchases, organization redesigns Database activity– physical database design (define database to DBMS, physical data organization, database processing programs)

38. Chapter 1 © 2013 Pearson Education, Inc. Publishing as Prentice Hall SYSTEMS DEVELOPMENT LIFE CYCLE (SEE ALSO FIGURE 1-7) (CONT.) 38 Planning Analysis Physical Design Implementation Maintenance Logical Design Implementation Purpose–programming, testing, training, installation, documenting Deliverable–operational programs, documentation, training materials Database activity– database implementation, including coded programs, documentation, installation and conversion

39. Chapter 1 © 2013 Pearson Education, Inc. Publishing as Prentice Hall SYSTEMS DEVELOPMENT LIFE CYCLE (SEE ALSO FIGURE 1-7) (CONT.) 39 Planning Analysis Physical Design Implementation Maintenance Logical Design Maintenance Purpose–monitor, repair, enhance Deliverable–periodic audits Database activity– database maintenance, performance analysis and tuning, error corrections

40. Chapter 1 © 2013 Pearson Education, Inc. Publishing as Prentice Hall Database Development Activities Identify Project Initiate and Plan Analyze Logical Design Physical Design Implementation Maintenance Enterprise Modeling Conceptual Data Modeling Logical DB Design Physical DB Design/Creation DB Implementation DB Maintenance SDLC

41. Chapter 1 © 2013 Pearson Education, Inc. Publishing as Prentice Hall  First step in the database development process  Specifies scope and general content  Overall picture of organizational data at high level of abstraction  Entity-relationship diagram  Descriptions of entity types  Relationships between entities  Business rules 41

42. Chapter 1 © 2013 Pearson Education, Inc. Publishing as Prentice Hall  Show interrelationships between objects.  Location-to-Function  Unit-to-Function  Information System-to-Data Entity  Supporting Function-to-Data Entity  Information System-to-Objective

43. Chapter 1 © 2013 Pearson Education, Inc. Publishing as Prentice Hall

44. Chapter 1 © 2013 Pearson Education, Inc. Publishing as Prentice Hall

45. Chapter 1 © 2013 Pearson Education, Inc. Publishing as Prentice Hall

46. Chapter 1 © 2013 Pearson Education, Inc. Publishing as Prentice Hall  A model which includes:  overall range of organizational databases  general contents of organizational databases  Built as part of IS planning for the organization and not the design of a particular database  One part of an organization’s overall information systems architecture (ISA) Enterprise Modeling Conceptual Data Modeling Logical DB Design Physical DB Design/Creation DB Implementation DB Maintenance

47. Chapter 1 © 2013 Pearson Education, Inc. Publishing as Prentice Hall  Determine user requirements  Determine business rules  Build conceptual data model  outcome is an entity- relationship diagram or similar communication tool  population of repository Enterprise Modeling Conceptual Data Modeling Logical DB Design Physical DB Design/Creation DB Implementation DB Maintenance

48. Chapter 1 © 2013 Pearson Education, Inc. Publishing as Prentice Hall  Select logical database model  commit to a database alternative  Map Entity- Relationship Diagrams  Normalize data structures  Specify business rules Enterprise Modeling Conceptual Data Modeling Logical DB Design Physical DB Design/Creation DB Implementation DB Maintenance

49. Chapter 1 © 2013 Pearson Education, Inc. Publishing as Prentice Hall  Select DBMS  Select storage devices  Determine access methods  Design files and indexes  Determine database distribution  Specify update strategies Enterprise Modeling Conceptual Data Modeling Logical DB Design Physical DB Design/Creation DB Implementation DB Maintenance

50. Chapter 1 © 2013 Pearson Education, Inc. Publishing as Prentice Hall  Code and test database processing programs  Complete documentation  Install database and convert data Enterprise Modeling Conceptual Data Modeling Logical DB Design Physical DB Design/Creation DB Implementation DB Maintenance

51. Chapter 1 © 2013 Pearson Education, Inc. Publishing as Prentice Hall  Analyze database and applications to ensure evolving information requirements are being met  Tune database for improved performance  Fix errors  Provide data recovery when needed Enterprise Modeling Conceptual Data Modeling Logical DB Design Physical DB Design/Creation DB Implementation DB Maintenance

52. 52 Prototyping Database Methodology (Figure 1-8) 52 Chapter 1 © 2013 Pearson Education, Inc. Publishing as Prentice Hall

53. 53 Prototyping Database Methodology (Figure 1-8) (cont.) 53 Chapter 1 © 2013 Pearson Education, Inc. Publishing as Prentice Hall

54. 54 Prototyping Database Methodology (Figure 1-8) (cont.) 54 Chapter 1 © 2013 Pearson Education, Inc. Publishing as Prentice Hall

55. 55 Prototyping Database Methodology (Figure 1-8) (cont.)

56. 56 Prototyping Database Methodology (Figure 1-8) (cont.) 56 Chapter 1 © 2013 Pearson Education, Inc. Publishing as Prentice Hall

57. Chapter 1 © 2013 Pearson Education, Inc. Publishing as Prentice Hall DATABASE SCHEMA  External Schema  User Views  Subsets of Conceptual Schema  Can be determined from business-function/data entity matrices  DBA determines schema for different users  Conceptual Schema  E-R models–covered in Chapters 2 and 3  Internal Schema  Logical structures–covered in Chapter 4  Physical structures–covered in Chapter 5 57

58. 58 Different people have different views of the database…these are the external schema The internal schema is the underlying design and implementation Figure 1-9 Three-schema architecture 58 Chapter 1 © 2013 Pearson Education, Inc. Publishing as Prentice Hall

59. Chapter 1 © 2013 Pearson Education, Inc. Publishing as Prentice Hall MANAGING PROJECTS  Project–a planned undertaking of related activities to reach an objective that has a beginning and an end  Initiated and planned in planning stage of SDLC  Executed during analysis, design, and implementation  Closed at the end of implementation 59

60. Chapter 1 © 2013 Pearson Education, Inc. Publishing as Prentice Hall MANAGING PROJECTS: PEOPLE INVOLVED  Business analysts  Systems analysts  Database analysts and data modelers  Users  Programmers  Database architects  Data administrators  Project managers  Other technical experts 60

61. Chapter 1 © 2013 Pearson Education, Inc. Publishing as Prentice Hall EVOLUTION OF DATABASE SYSTEMS  Driven by four main objectives:  Need for program-data independence  reduced maintenance  Desire to manage more complex data types and structures  Ease of data access for less technical personnel  Need for more powerful decision support platforms 61

62. Chapter 1 © 2013 Pearson Education, Inc. Publishing as Prentice Hall 62 Figure 1-10a Evolution of database technologies

63. Chapter 1 © 2013 Pearson Education, Inc. Publishing as Prentice Hall 63 Figure 1-10b Database architectures

64. Chapter 1 © 2013 Pearson Education, Inc. Publishing as Prentice Hall 64 Figure 1-10b Database architectures (cont.)

65. Chapter 1 © 2013 Pearson Education, Inc. Publishing as Prentice Hall 65 Figure 1-10b Database architectures (cont.)

66. Chapter 1 © 2013 Pearson Education, Inc. Publishing as Prentice Hall THE RANGE OF DATABASE APPLICATIONS  Personal databases  Two-tier and N-tier Client/Server databases  Enterprise applications  Enterprise resource planning (ERP) systems  Data warehousing implementations 66

67. 67 Figure 1-11 Two-tier database with local area network 67 Chapter 1 © 2013 Pearson Education, Inc. Publishing as Prentice Hall

68. 68 Figure 1-12 Three-tiered client/server database architecture 68 Chapter 1 © 2013 Pearson Education, Inc. Publishing as Prentice Hall

69. Chapter 1 © 2013 Pearson Education, Inc. Publishing as Prentice Hall ENTERPRISE DATABASE APPLICATIONS  Enterprise Resource Planning (ERP)  Integrate all enterprise functions (manufacturing, finance, sales, marketing, inventory, accounting, human resources)  Data Warehouse  Integrated decision support system derived from various operational databases 69

70. 70 FIGURE 1-13 Computer System for Pine Valley Furniture Company 70 Chapter 1 © 2013 Pearson Education, Inc. Publishing as Prentice Hall

71. Chapter 1 © 2013 Pearson Education, Inc. Publishing as Prentice Hall

72. 72 Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall