1. Fanny Widadie, S.P, M.Agr 1 Database Management Systems

2. 2 The Data Hierarchy ► Data field is the smallest unit of data. ► Record is a collection of related data fields. ► File is a collection of related records. ► Database is a collection of related files.  General definition  Restrictive definition

3. 3 Database ► Table of rows and columns can be represented in a spreadsheet. ► Relational database structure is conceptually similar to a collection of related tables. ► Flat file is a table that does not have repeating columns; 1 st normal form. ► Normalization is a formal process for eliminating redundant data fields while preserving the ability of the database to add, delete, and modify records without causing errors.

4. 4 Figure 6.1 Spreadsheet Example of the COURSE Table

5. 5 Database (Cont’d) ► Key in a table is a field (or combination of fields) that contain a value that uniquely identifies each record in the table. ► Candidate key is a field that uniquely identifies each table row but is not the chosen key. ► Relating tables is done through sharing a common field and the value of the field determines which rows in the tables are logically joined.

6. 6 Database Structures ► Database management system (DBMS) is a software application that stores the structure of the database, the data itself, relationships among data in the database, and forms and reports pertaining to the database.  Self-describing set of related data.

7. 7 Hierarchical Database Structures ► Hierarchical is formed by data groups, subgroups, and further subgroups; like branches on a tree.  Worked well with TPSs  Utilized computer resources efficiently ► Network allows retrieval of specific records; allows a given record to point to any other record in the database.

8. 8 Figure 6.2 The Hierarchical Structure Between the DEPARTMENT and COURSE Tables

9. 9 Database Structures (Cont’d) ► Relational is when the relationship between tables are implicit. ► Physical relationship is when the database structure (hierarchical, network) rely on storage addresses. ► Implicit relationship is when the database structure (relational) can be implied from the data.

10. 10 A Relational Database Example ► A database named Schedule has been created from tables used earlier in the chapter and some others ► The database is implemented in Microsoft Access 2002 (also known as Access XP). ► Databases break information into multiple tables because if information were stored in a single table, many data field values would be duplicated.

11. 11 The Schedule Database ► The example is implemented on Microsoft Access DBMS but would be similar on any relational DBMS product. ► The COURSE table in Access (Figure 6.4) is a list of data field values. The table itself had to be defined in Access before values were entered into the data fields. ► Figure 6.5 shows the definition of the Code field. ► Figure 6.6 illustrates that Abbreviation field values will be looked up from a list of values in the DEPARTMENT table. ► Table 6.7 shows a single table of course and department fields before they were separated into different tables.

12. 12 Figure 6.4 The COURSE Table in Access

13. 13 Figure 6.5 Defining the CODE Field

14. © 2007 by Prentice HallManagement Information Systems, 10/e Raymond McLeod and George Schell 14 Figure 6.6 Look-up Values

15. 15 Table 6.7 Unseperated Table of Course and Department Data Fields

16. 16 Figure 6.7 Access View of Tables, Fields, and their Relationships

17. 17 The Database Concept ► Database concept is the logical integration of records across multiple physical locations. ► Data independence is the ability to make changes in the data structure without making changes to the application programs that access the data. ► Data dictionary includes the definition of the data stored within the database and controlled by the database management system.

18. 18 Creating a Database ► Determine data that needs to be collected and stored is a key step. ► Process-oriented approach  Define the problem.  Identify necessary decisions.  Describe information needs.  Determine the necessary processing.  Specify data needs.

19. 19 Determine Data Needs ► Enterprise modeling approach takes a broad view of the firm’s data resources; all areas are considered, and synergy of data resources between business areas can be leveraged.  Result: Enterprise data model

20. © 2007 by Prentice Hall20 Figure 6.8 Creating an Enterprise Data Model

21. 21 Data Modeling Techniques ► Entity-relationship diagrams (ERDs) is a graphical representation of data in entities and the relationships between entities. ► Entity is a conceptual collection of related data fields. ► Relationship is defined between entities.  One-to-one – 1:1  One-to-many – 1:M  Many-to-many – M:N

22. 22 Figure 6.11 Entity-Relationship Diagram

23. 23 Diagramming Techniques ► Class Diagram is a graphical representation of both the data used in an application and the actions associated with the data; object-oriented design model. ► Objects are the data, actions taken on the data, and relationship between objects. ► Class diagrams consist of the named class, fields in the class, and actions (methods) that act upon the class.

24. 24 Figure 6.13 Class Diagram

25. 25 Using the Database ► Forms show one record at a time and can be used to add, delete, or modify database records.  Navigation  Accuracy  Consistency  Filtering  Subforms

26. 26 Figure 6.15 Combined Data Entry Form for the COURSE and PROJECT Tables

27. 27 Using the Database (Cont’d) ► Reports are aggregated data from the database that are formatted in a manner that aids decision making. ► Queries is a request for the database to display selected records. ► Query-by-example (QBE) presents a standardized form that the user completes so the system can generate a true query.

28. 28 Figure 6.16 Report of Departments Showing Courses Offered and Course Projects