1. Database Management Systems
COMP 281 / ITEC 281 / MIS 281
Fall 2005
Instructor: Justin M. Wang

2. Course Logistics Instructor information Roster Materials
Communications
Grading policy
Submission & return policy
Academic integrity
Assignment submission date Maximum grade( % of total possible points)
1 week late 90 %
More than 1 week late 50 %
Except on the week 14
Database Management Systems

3. Course Introduction Course schedules and six modules Course outcomes
Student responsibilities and expectations
Course web site demonstration
Basic Database Concepts. The relationship of a database to the organizational structure is also discussed.
Entity Relationship Diagrams. This is the diagramming technique you will use for the conceptual design of your database system.
Physical Database Structure. This will be created using Structured Query Language (SQL) and Oracle.
Logical and Physical Design of the Database Application. This topic includes normalization and denormalization.
Data Warehousing. This topic includes data warehousing techniques and terminology.
Application Development of the Database System. This topic will include the components required for using these applications such as the architecture and the data access tools.
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4. Activity: Group Development
Teams should be approximately 3 to 4 students
Exchange contact information and communication methods
Teams will be used primarily to review other team members’ designs
A member from each team sends me an about your group information
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5. Module 1 Database Concepts

6. Chapter 1 Database Systems
Module 1: Database Concepts

7. Preview Data vs. information Database, different types of databases
Database design
Databases evolving
Database systems vs. file systems
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8. Data vs. Information Data: Information:
Raw facts; building blocks of information
Unprocessed information
Information:
Data processed to reveal meaning
Accurate, relevant, and timely information is key to good decision making
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9. Database Database—shared, integrated computer structure that houses:
End user data (raw facts)
Metadata (data about data)
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10. Database Management System (DBMS)
Collection of programs that manages database structure and controls access to data
Possible to share data among multiple applications or users
Makes data management more efficient and effective
End users have better access to more and better-managed data
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11. DBMS Interfaces
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12. Types of Databases Single-user: only one user at a time
Desktop: single-user database running on a personal computer
Multi-user: multiple users concurrently
Workgroup: a small group of users
Enterprise: a large group of users
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13. Internet, Intranet, and Extranet Databases
Web-enabled
Examples reflect B2C, B2B
Large number of potential users
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14. Location of Databases Centralized: Distributed:
Supports data located at a single site
Distributed:
Supports data distributed across several sites
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15. Uses of Databases Transactional (OLTP): Data warehouse (OLAP):
Supports a company’s day-to-day operations
Data warehouse (OLAP):
Stores data used to make tactical or strategic decisions
Often used to store historical data
Structure is quite different
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16. Database Design Defines the database’s expected use
Different approach needed for different types of databases
Avoid redundant data
Poorly designed database generates errors  leads to bad decisions  can lead to failure of organization
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17. Manual File Systems
Traditionally composed of collection of file folders kept in file cabinet
Organized with folders (ideally logically related)
Were adequate for small amounts of data with few reporting requirements
Lacked scalability
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18. Computer File System Could be technically complex
DP specialists created file structures, wrote software, and designed application programs
Resulted in numerous “home-grown” systems being created
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19. Basic File Terminology
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20. A Simple File System
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21. Problems with File System
Requires extensive programming in a third-generation language (3GL)
Structural dependence
Data dependence: logical and physical format
Limited data sharing
Data redundancy
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22. Database vs. File System
Problems inherent in file systems make using a database system desirable
File system
Many separate and unrelated files
Database
Logically related data stored in a single logical data repository
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23. Contrasting Database and File Systems
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24. DBMS Functions Data dictionary management Data storage management
Data transformation and presentation
Security management
Multi-user access control
Backup and recovery management
Data integrity management
Database access languages and application programming interfaces
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25. Disadvantages of DB Approach
Higher initial cost for specialized software (DBMS)
Higher learning curve for new DBMS software
Organizational conflict on data definitions, data formats and coding
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26. Evolution of database technologies
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27. Summary of Chapter 1 Information is derived from data
To implement and manage a database, use a DBMS
Database design defines its structure
Databases were preceded by file systems
Because file systems lack a DBMS, file management lacks scalability
DBMS were developed to address file systems’ inherent weaknesses
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28. Module 1: Database Concepts
Chapter 2 Data Model
Module 1: Database Concepts

29. Preview Basic data-modeling building blocks
Major data models, and their advantages and disadvantages
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30. Data Models
Relatively simple representation of complex real-world data structures
Communications tool among the designer, the applications programmer, and the end user
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31. Data Model Building Blocks
Entity is anything about which data are to be collected and stored
Attribute is a characteristic of an entity
Relationship describes an association among (two or more) entities
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32. The Evolution of Data Models
Hierarchical
Network
Relational
Entity relationship
Object oriented
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33. The Hierarchical Model
GUAM (Generalized Update Access Method): many smaller parts would come together as components of still larger components
Information Management System (IMS): world’s leading mainframe hierarchical database system in the 1970s and early 1980s
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34. A Hierarchical Structure
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35. The Network Model Created to
Represent complex data relationships more effectively
Improve database performance
Impose a database standard defined by Database Task Group (DBTG)
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36. Network Model Components
Schema - conceptual organization of entire database
Subschema - database portion “seen” by the application programs
Schema Data Definition Language (DDL) - schema components
Subschema DDL - allows application programs to access database components
DML - manipulates database contents
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37. A Network Data Model
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38. The Relational Model Developed by Codd (IBM) in 1970
Considered ingenious but impractical in 1970
Conceptually simple
Today, microcomputers can run sophisticated relational database software
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39. The Relational Model—Basic Structure
Relational Database Management System (RDBMS)
Table (relations)
Relational schema - Visual representation of relational database’s entities, attributes and relationships
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40. A Relational Schema
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41. The Entity Relationship Model
Widely accepted and adapted graphical tool for data modeling
Introduced by Chen in 1976
Graphical representation of entities and their relationships in a database structure
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42. The ER Model - Basic Structure
Entity relationship diagram (ERD)
Entity instance (or occurrence) is row in table
Types of relationships
Diamond connected to related entities through a relationship line
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43. Relationships: Basic Chen ERD
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44. Relationships: Crow’s Foot ERD
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45. The Object Oriented Model
Semantic data model (SDM) developed by Hammer and McLeod in 1981
Modeled both data and their relationships in a single structure known as an object
Basis of object oriented data model (OODM)
OODM becomes the basis for the object oriented database management system (OODBMS)
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46. OODM - Basic Structure Object: abstraction of a real-world entity
Attributes describe the properties of an object
Objects that share similar characteristics are grouped in classes
Inheritance is the ability of an object within the class hierarchy to inherit the attributes and methods of classes above it
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47. A Comparison of the OO Model and the ER Model
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48. Development of Data Models
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49. Summary of Chapter 2
A data model is a (relatively) simple abstraction of a complex real-world data-gathering environment
Basic data modeling components are:
Entities
Attributes
Relationships
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50. Summary of Chapter 2 (cont’d)
Hierarchical model - Based on a tree structure composed of a root segment, parent segments, and child segments
Network model attempts to deal with many of the hierarchical model’s limitations
Relational model - Current database implementation standard
Object is basic modeling structure of object oriented model
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51. Wrap Up Assignment 1-1 Module 2 – Database design concepts
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