1. Management Information Systems, 10/e
Raymond McLeod Jr. and George P. Schell
© 2007 by Prentice Hall
Management Information Systems, 10/e Raymond McLeod and George Schell

2. Database Management Systems
Chapter 6
Database Management Systems
© 2007 by Prentice Hall
Management Information Systems, 10/e Raymond McLeod and George Schell

3. Management Information Systems, 10/e Raymond McLeod and George Schell
Learning Objectives
Understand the hierarchy of data.
Understand database structures and how they work.
Know how to relate tables together in a database.
Recognize the difference between a database and a database management system.
Understand the database concept.
Know two basic methods for determining data needs.
© 2007 by Prentice Hall
Management Information Systems, 10/e Raymond McLeod and George Schell

4. Learning Objectives (Cont’d)
Understand entity-relationship diagrams and class diagrams.
Know the basics of reports and forms.
Understand the basic difference between structured query language and query-by-example.
Know about the important personnel who are associated with databases.
Know the advantages and costs of database management systems.
© 2007 by Prentice Hall
Management Information Systems, 10/e Raymond McLeod and George Schell

5. Management Information Systems, 10/e Raymond McLeod and George Schell
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
© 2007 by Prentice Hall
Management Information Systems, 10/e Raymond McLeod and George Schell

6. Management Information Systems, 10/e Raymond McLeod and George Schell
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; 1st 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.
© 2007 by Prentice Hall
Management Information Systems, 10/e Raymond McLeod and George Schell

7. Figure 6.1 Spreadsheet Example of the COURSE Table
© 2007 by Prentice Hall
Management Information Systems, 10/e Raymond McLeod and George Schell

8. Management Information Systems, 10/e Raymond McLeod and George Schell
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.
© 2007 by Prentice Hall
Management Information Systems, 10/e Raymond McLeod and George Schell

9. Management Information Systems, 10/e Raymond McLeod and George Schell
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.
© 2007 by Prentice Hall
Management Information Systems, 10/e Raymond McLeod and George Schell

10. 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.
© 2007 by Prentice Hall
Management Information Systems, 10/e Raymond McLeod and George Schell

11. Management Information Systems, 10/e Raymond McLeod and George Schell
Figure 6.2 The Hierarchical Structure Between the DEPARTMENT and COURSE Tables
© 2007 by Prentice Hall
Management Information Systems, 10/e Raymond McLeod and George Schell

12. 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.
© 2007 by Prentice Hall
Management Information Systems, 10/e Raymond McLeod and George Schell

13. 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.
© 2007 by Prentice Hall
Management Information Systems, 10/e Raymond McLeod and George Schell

14. Management Information Systems, 10/e Raymond McLeod and George Schell
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.
© 2007 by Prentice Hall
Management Information Systems, 10/e Raymond McLeod and George Schell

15. Figure 6.4 The COURSE Table in Access
© 2007 by Prentice Hall
Management Information Systems, 10/e Raymond McLeod and George Schell

16. Figure 6.5 Defining the CODE Field
© 2007 by Prentice Hall
Management Information Systems, 10/e Raymond McLeod and George Schell

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

18. Table 6.7 Unseperated Table of Course and Department Data Fields
© 2007 by Prentice Hall
Management Information Systems, 10/e Raymond McLeod and George Schell

19. Figure 6.7 Access View of Tables, Fields, and their Relationships
© 2007 by Prentice Hall
Management Information Systems, 10/e Raymond McLeod and George Schell

20. Management Information Systems, 10/e Raymond McLeod and George Schell
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.
© 2007 by Prentice Hall
Management Information Systems, 10/e Raymond McLeod and George Schell

21. Management Information Systems, 10/e Raymond McLeod and George Schell
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.
© 2007 by Prentice Hall
Management Information Systems, 10/e Raymond McLeod and George Schell

22. Management Information Systems, 10/e Raymond McLeod and George Schell
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
© 2007 by Prentice Hall
Management Information Systems, 10/e Raymond McLeod and George Schell

23. Figure 6.8 Creating an Enterprise Data Model
© 2007 by Prentice Hall
Management Information Systems, 10/e Raymond McLeod and George Schell

24. 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
© 2007 by Prentice Hall
Management Information Systems, 10/e Raymond McLeod and George Schell

25. Figure 6.11 Entity-Relationship Diagram
© 2007 by Prentice Hall
Management Information Systems, 10/e Raymond McLeod and George Schell

26. 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.
© 2007 by Prentice Hall
Management Information Systems, 10/e Raymond McLeod and George Schell

27. Management Information Systems, 10/e Raymond McLeod and George Schell
Figure 6.13 Class Diagram
© 2007 by Prentice Hall
Management Information Systems, 10/e Raymond McLeod and George Schell

28. Management Information Systems, 10/e Raymond McLeod and George Schell
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
© 2007 by Prentice Hall
Management Information Systems, 10/e Raymond McLeod and George Schell

29. Figure 6.15 Combined Data Entry Form for the COURSE and PROJECT Tables
© 2007 by Prentice Hall
Management Information Systems, 10/e Raymond McLeod and George Schell

30. 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.
© 2007 by Prentice Hall
Management Information Systems, 10/e Raymond McLeod and George Schell

31. Management Information Systems, 10/e Raymond McLeod and George Schell
Figure 6.16 Report of Departments Showing Courses Offered and Course Projects
© 2007 by Prentice Hall
Management Information Systems, 10/e Raymond McLeod and George Schell

32. Structured Query Language
Structured query language (SQL) is the code that RDBMSs use to perform their database tasks.
Method of choice for interacting with Web-based databases.
Writing SQL statements are not difficult for most manager’s data needs.
© 2007 by Prentice Hall
Management Information Systems, 10/e Raymond McLeod and George Schell

33. Management Information Systems, 10/e Raymond McLeod and George Schell
Figure 6.20 Structured Query Language Code to Find Projects for the MIS105 Course
© 2007 by Prentice Hall
Management Information Systems, 10/e Raymond McLeod and George Schell

34. Advanced Database Processing
On-line analytical processing (OLAP) allows data analysis similar to statistical cross-tabulation.
Data mining, data marts, and data warehousing focus on methodologies that offer users quick access to aggregated data specific to their decision-making needs.
Knowledge discovery analyzes data usage and data commonality among different tables.
© 2007 by Prentice Hall
Management Information Systems, 10/e Raymond McLeod and George Schell

35. Management Information Systems, 10/e Raymond McLeod and George Schell
Database Personnel
Database Administrator (DBA) is an expert in developing, providing, and securing databases; duties include:
Database planning;
Database implementation;
Database operation;
Database security.
© 2007 by Prentice Hall
Management Information Systems, 10/e Raymond McLeod and George Schell

36. Database Personnel (Cont’d)
Database programmer writes code to strip and/or aggregate data from the database
High level of specialization and selection
End user generates reports and forms, post queries to the database, and use results from their database inquiries to make decisions that affect the firm and its environmental constituents.
© 2007 by Prentice Hall
Management Information Systems, 10/e Raymond McLeod and George Schell

37. Management Information Systems, 10/e Raymond McLeod and George Schell
DBMSs in Perspective
DBMS Advantages
Reduce data redundancy.
Achieve data independence.
Retrieve data and information rapidly.
Improve security.
DBMS Disadvantages
Obtain expensive software.
Obtain a large hardware configuration.
Hire and maintain a DBA staff.
© 2007 by Prentice Hall
Management Information Systems, 10/e Raymond McLeod and George Schell