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Transcript 
Chapter 9 & 10
Database Planning, Design and
Administration
• Database Application Lifecycle
• DBMS Selection
• Database Administration
Database Application Lifecycles
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Database planning
Systems definition
Requirements collection and analysis
Database design
DBMS selection
Application design
Prototyping
Implementation
Data conversion and loading
Testing
Operational maintenance
Database Planning
• Business goals and plans
• Information systems needs
• Corporate data model
– user needs
– legal requirement
System Definition
• Scope & boundaries
• Applications
Requirement collection
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Interview
Questionnaires
Observation
Documentation
Experience
Requirement Analysis
• Data centered approach
– Entity-Relationship (ER) diagram
– Normalization
• Process center approach
– Structured Analysis and Design (SAD)
– Data Flow Diagram (DFD)
– Hierarchical Input Process Output (HIPO)
Database Design
• Approaches
– Top-down
– Bottom-up or inside-out
– Mixed
• Components
– Logical
– Physical
Logical Database Design
• Steps
– Conceptual data model
– Logical data model (normalized & specific data
model)
– Global logical data model
• Approaches
– Centralized
– View integration
Optimal Logical Data Model
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Structure validity
Simplicity
Expressability
Nonredundancy
Shareability
Extensibility
Integrity
Diagrammatic representation
Physical Database Design
• Storage structure
• Access method
• Security protection
Application Design
• Transactions
– Retrieval
– Update
– Mixed
• User interface (forms & reports)
– Logical
– Simple
– Error handling
– Help
– Meaningful
– Consistency
– Status
CASE Tools
• Computer-Aided Software Engineering (CASE)
• Types
– Upper-Case: planning to design
– Lower-Case: implementing, test, performance
– Integrated-Case
• Benefits: Productivity (effectiveness and
efficiency)
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Standard
Integration (repository)
Support structured methods
Consistency
Automation
Prototyping
• Working model
• Pros
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Define user’s requirements
Quick
Feasibility test
Low cost and risk, new technology
• Cons
– Costs
Implementation
• Data definition language (DDL)
• Data manipulation language (DML) or
embedded DML
• Security & integrity control
Data Conversion and Loading
• Actual data conversion
• Bridge
Testing
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Top-down
Bottom-up
Thread
Stress
Operational Maintenance
• Monitoring
• Tuning
• Upgrading
DBMS Selection Criteria
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Development or end-user language
Data structure
Flexibility
Security & Privacy
Restart & Recovery
Integrity
Hardware & software requirements
Performance
Monitoring
Ease of use
Data dictionary
Teleprocessing
Design tools
Vendor support
Costs
Future
Database Administration Role
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Physical database design
Security & integrity control
Performance monitoring
Tuning database
Data Administration Role
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Planning
Developing and maintaining standard
Developing policy & procedure
Design conceptual and logical database
Assignment
• Review chapter 9-10
• Read chapter 11-12
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