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

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Presentation on theme: "© 2007 by Prentice Hall Management Information Systems, 10/e Raymond McLeod and George Schell 1 Management Information Systems, 10/e Raymond McLeod Jr."— Presentation transcript:

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

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

3 © 2007 by Prentice HallManagement Information Systems, 10/e Raymond McLeod and George Schell 3 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.

4 © 2007 by Prentice HallManagement 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.

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

6 © 2007 by Prentice HallManagement Information Systems, 10/e Raymond McLeod and George Schell 6 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.

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

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

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

10 © 2007 by Prentice HallManagement 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.

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

12 © 2007 by Prentice HallManagement 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.

13 © 2007 by Prentice HallManagement 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.

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

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

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

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

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

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

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

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

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

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

24 © 2007 by Prentice HallManagement 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

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

26 © 2007 by Prentice HallManagement 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.

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

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

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

30 © 2007 by Prentice HallManagement 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.

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

32 © 2007 by Prentice HallManagement 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.

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

34 © 2007 by Prentice HallManagement 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.

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

36 © 2007 by Prentice HallManagement 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.

37 © 2007 by Prentice HallManagement Information Systems, 10/e Raymond McLeod and George Schell 37 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.


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