ITM 354 Database Management

1. ITM 354 Database Management • Instructor: Dr. Nancy Deng • xuefei@hawaii.edu; (808) 956-7580 • Visit Course URL: • http://ndeng.shidler.hawaii.edu/ITM354.htm • Your Comments/Suggestions

2. Chapter 1:The Database Environment Modern Database Management 8th Edition Jeffrey A. Hoffer, Mary B. Prescott, Fred R. McFadden © 2007 by Prentice Hall

3. Data Matters! • No. 1 World's Most Admired Airline (FORTUNE,2007) • No. 1 2007 America's Most Admired airline (FORTUNE,2007) .

4. Chapter 1 Objectives • 1) Definition of terms • 2) Limitations of conventional file processing • 3) Costs and risks of databases • 4) Elements of database approach • 6) Components of database environment • 7) Evolution of database systems

5. 1) Definitions: Data vs. Information • Data: • stored representations of meaningful objects and events • Structured: numbers, text, dates • Unstructured: images, video, documents • Example: data for an auto repair shop • Information: • data processed to increase knowledge in the person using the data

6. Figure 1-1a Data in context Context helps users understand data

7. Figure 1-1b Summarized data

8. Database: organized collection of logically related data

9. Definition: Metadata • Metadata: data that describes the properties and context of user data. • but separate from that data; • Stored as part of the database. ---including data types, field sizes, allowable values, and data context

11. Your Turn: Data or Metadata

12. Duplicate Data 2) Conventional file processing systems at Pine Valley Furniture Company

13. 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

14. Problems with Data Dependency • Each application programmer must • maintain his/her own data • include code for the metadata of each file • have its own processing routines for reading, inserting, updating, and deleting data • Lack of coordination and central control • Non-standard file formats

15. 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

16. Solution:Database Management System (DBMS) • A software system that is used to create, maintain, and provide controlled access to user databases Order Filing System Central database Contains employee, order, inventory, pricing, and customer data Invoicing System DBMS Payroll System DBMS manages data resources like an operating system manages hardware resources

17. Typical DBMS Functionality • Define a particular database in terms of its data types, structures, and constraints • Construct or Load the initial database contents on a secondary storage medium • Manipulating the database: • Retrieval: Querying, generating reports • Modification: Insertions, deletions and updates to its content • Accessing the database through Web applications • Processing and Sharing by a set of concurrent users and application programs – yet, keeping all data valid and consistent

18. Advantages of the Database Approach • Program-data independence • Planned data redundancy • Improved • Data quality • data consistency • data sharing • Data accessibility and responsiveness • development productivity • Enforcement of standards • Improved decision support

19. 3) Costs and Risks of the Database Approach • New, specialized personnel • Installation and management cost and complexity • Conversion costs • Need for explicit backup and recovery • Organizational conflict

20. 4) Elements of the Database Approach • 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 • Relational Databases • Database technology involving tables (relations) representing entities and primary/foreign keys representing relationships

21. Segment of an Enterprise Data Model Segment of a Project-Level Data Model

22. One customer may place many orders, but each order is placed by a single customer  One-to-many relationship

23. One order has many order lines; each order line is associated with a single order  One-to-many relationship

24. One product can be in many order lines, each order line refers to a single product  One-to-many relationship

25. Therefore, one order involves many products and one product is involved in many orders  Many-to-many relationship

26. Your Turn: Enterprise Data Model Store • Q1: relationship between Pet and Store? • Q2: relationship between Customer and Pet? • Q3: Should there be a relationship between Customer and Store? Customer Pet

27. Revisit: Conventional file processing systems at Pine Valley Furniture Company

28. Figure 1-4 Enterprise data model for Figure 1-3 segments

29. Figure 1-5 Components of the Database Environment

30. 5) Components of the Database Environment • 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

31. The Range of Database Applications • Personal databases • Workgroup databases • Departmental/divisional databases • Enterprise database • Web-enabled database

33. Figure 1-6 Typical data from a personal database

34. Figure 1-7 Workgroup database with wireless local area network

35. 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

36. Evolution of DB Systems

37. Figure 1-8 An enterprise data warehouse

38. 6) Evolution of DBMS • 1st Generation: Early Database Applications • 1960s:The Hierarchical and Network Models were introduced • 1970s: They became dominated. • A bulk of the worldwide database processing still occurs using these models, particularly, the hierarchical model. • 2nd Generation: Relational Model based Systems • Originally introduced in 1970, a paper by E. F. Codd • IBM Research and several universities. • 1980s: Relational DBMS Products emerged.

39. Evolution of DBMS(continued) • 3rd Generation: Object-oriented Applications • 1990s: Object-Oriented Database Management Systems (OODBMSs) for complex data processing in CAD and other applications. • Object-relational DBMSs (ORDBMSs) • Extended relational systems add further capabilities (e.g. for multimedia data, XML, and other data types)